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1. Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches

Author

Christophe, Clément, Kanithi, Praveen K, Munjal, Prateek, Raha, Tathagata, Hayat, Nasir, Rajan, Ronnie, Al-Mahrooqi, Ahmed, Gupta, Avani, Salman, Muhammad Umar, Gosal, Gurpreet, Kanakiya, Bhargav, Chen, Charles, Vassilieva, Natalia, Amor, Boulbaba Ben, Pimentel, Marco AF, and Khan, Shadab

Subjects
Computer Science - Computation and Language
Abstract

This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs). We developed and refined a series of LLMs, based on the Llama-2 architecture, specifically designed to enhance medical knowledge retrieval, reasoning, and question-answering capabilities. Our experiments systematically evaluate the effectiveness of these tuning strategies across various well-known medical benchmarks. Notably, our medical LLM Med42 showed an accuracy level of 72% on the US Medical Licensing Examination (USMLE) datasets, setting a new standard in performance for openly available medical LLMs. Through this comparative analysis, we aim to identify the most effective and efficient method for fine-tuning LLMs in the medical domain, thereby contributing significantly to the advancement of AI-driven healthcare applications., Comment: Published at AAAI 2024 Spring Symposium - Clinical Foundation Models

Published
2024

3. Highly accurate blood test for Alzheimer’s disease is similar or superior to clinical cerebrospinal fluid tests

Author

Barthélemy, Nicolas R, Salvadó, Gemma, Schindler, Suzanne E, He, Yingxin, Janelidze, Shorena, Collij, Lyduine E, Saef, Benjamin, Henson, Rachel L, Chen, Charles D, Gordon, Brian A, Li, Yan, La Joie, Renaud, Benzinger, Tammie LS, Morris, John C, Mattsson-Carlgren, Niklas, Palmqvist, Sebastian, Ossenkoppele, Rik, Rabinovici, Gil D, Stomrud, Erik, Bateman, Randall J, and Hansson, Oskar

Subjects
Biomedical and Clinical Sciences, Health Sciences, Neurodegenerative, Dementia, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Aging, Neurosciences, Brain Disorders, Alzheimer's Disease, 4.2 Evaluation of markers and technologies, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Neurological, Humans, Alzheimer Disease, tau Proteins, Biomarkers, Amyloid beta-Peptides, Cognitive Dysfunction, Hematologic Tests, Positron-Emission Tomography, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Published
2024

4. Gemini: A Family of Highly Capable Multimodal Models

Author

Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Published
2023

10. Disease staging of Alzheimer’s disease using a CSF-based biomarker model

Author

Salvadó, Gemma, Horie, Kanta, Barthélemy, Nicolas R., Vogel, Jacob W., Pichet Binette, Alexa, Chen, Charles D., Aschenbrenner, Andrew J., Gordon, Brian A., Benzinger, Tammie L. S., Holtzman, David M., Morris, John C., Palmqvist, Sebastian, Stomrud, Erik, Janelidze, Shorena, Ossenkoppele, Rik, Schindler, Suzanne E., Bateman, Randall J., and Hansson, Oskar

Published
2024
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13. Exploratory Analysis of Multiple Labor Relations in China’s Internet Platform Economy

Author

CHEN, Charles Weizheng, LI, Hongli, HU, Dongmei, CHEN, Yuling, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Moutinho, Luiz, editor, Flavian, Carlos, editor, Li, Rita Yi Man, editor, and Zhou, Qiwei, editor

Published
2024
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18. Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

Author

Noble, James M., Day, Gregory S., Graff-Radford, Neill R., Voglein, Jonathan, Levin, Johannes, Allegri, Ricardo F., Mendez, Patricio Chrem, Surace, Ezequiel, Berman, Sarah B., Ikonomovic, Snezana, Nadkarni, Neelesh K., Lopera, Francisco, Ramirez, Laura, Aguillon, David, Leon, Yudy, Ramos, Claudia, Alzate, Diana, Baena, Ana, Londono, Natalia, Moreno, Sonia, Jucker, Mathias, Laske, Christoph, Kuder-Buletta, Elke, Graber-Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ikeuchi, Takeshi, Kasuga, Kensaku, Niimi, Yoshiki, Ishii, Kenji, Senda, Michio, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Fox, Nick C., Cash, Dave, Lee, Jae-Hong, Roh, Jee Hoon, Salloway, Stephen, Riddle, Meghan C., Menard, William, Bodge, Courtney, Surti, Mustafa, Takada, Leonel Tadao, Farlow, Martin, Chhatwal, Jasmeer P., Sanchez-Gonzalez, V.J., Orozco-Barajas, Maribel, Goate, Alison M., Renton, Alan E., Esposito, Bianca T., Karch, Celeste M., Marsh, Jacob, Cruchaga, Carlos, Fernanadez, Victoria, Gordon, Brian A., Fagan, Anne M., Jerome, Gina, Herries, Elizabeth, Llibre-Guerra, Jorge, Levey, Allan I., Johnson, Erik C.B., Seyfried, Nicholas T., Schofield, Peter R., Brooks, William S., Bechara, Jacob A., Bateman, Randall, McDade, Eric, Hassenstab, Jason, Perrin, Richard J., Franklin, Erin E., Benzinger, Tammie, Chen, Allison, Chen, Charles, Flores, Shaney, Friedrichsen, Nelly, Gordon, Brian, Hantler, Nancy, Hornbeck, Russ, Jarman, Steve, Keefe, Sarah, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, McKay, Nicole, Nicklaus, Joyce, Pulizos, Christine, Wang, Qing, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily, Candela, Madison, Smith, Hunter, Hobbs, Diana, Scott, Jalen, Xiong, Chengjie, Wang, Peter, Xu, Xiong, Li, Yan, Gremminger, Emily, Ma, Yinjiao, Bui, Ryan, Lu, Ruijin, Martins, Ralph, Sosa Ortiz, Ana Luisa, Daniels, Alisha, Courtney, Laura, Mori, Hiroshi, Supnet-Bell, Charlene, Xu, Jinbin, Ringman, John, Barthelemy, Nicolas, Morris, John, Smith, Jennifer, Doering, Stephanie, Chen, Charles D., Jarman, Stephen, Jackson, Kelley, Hornbeck, Russ C., Ances, Beau M., Aschenbrenner, Andrew J., Bateman, Randall J., Morris, John C., and Benzinger, Tammie L.S.

Published
2024
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19. Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer's disease: a cross-sectional study

Author

Boerwinkle, Anna H, Gordon, Brian A, Wisch, Julie, Flores, Shaney, Henson, Rachel L, Butt, Omar H, McKay, Nicole, Chen, Charles D, Benzinger, Tammie LS, Fagan, Anne M, Handen, Benjamin L, Christian, Bradley T, Head, Elizabeth, Mapstone, Mark, Rafii, Michael S, O'Bryant, Sid, Lai, Florence, Rosas, H Diana, Lee, Joseph H, Silverman, Wayne, Brickman, Adam M, Chhatwal, Jasmeer P, Cruchaga, Carlos, Perrin, Richard J, Xiong, Chengjie, Hassenstab, Jason, McDade, Eric, Bateman, Randall J, Ances, Beau M, Syndrome, Alzheimer's Biomarker Consortium-Down, Aizenstein, Howard J, Andrews, Howard F, Bell, Karen, Birn, Rasmus M, Bulova, Peter, Cheema, Amrita, Chen, Kewei, Clare, Isabel, Clark, Lorraine, Cohen, Ann D, Constantino, John N, Doran, Eric W, Feingold, Eleanor, Foroud, Tatiana M, Hartley, Sigan L, Hom, Christy, Honig, Lawrence, Ikonomovic, Milos D, Johnson, Sterling C, Jordan, Courtney, Kamboh, M Ilyas, Keator, David, Klunk, William E, Kofler, Julia K, Kreisl, William C, McHale, Sharon J Krinsky-, Lao, Patrick, Laymon, Charles, Lott, Ira T, Lupson, Victoria, Mathis, Chester A, Minhas, Davneet S, Nadkarni, Neelesh, Pang, Deborah, Petersen, Melissa, Price, Julie C, Pulsifer, Margaret, Reiman, Eric, Rizvi, Batool, Sabbagh, Marwan N, Schupf, Nicole, Tudorascu, Dana L, Tumuluru, Rameshwari, Tycko, Benjamin, Varadarajan, Badri, White, Desiree A, Yassa, Michael A, Zaman, Shahid, Zhang, Fan, Network, Dominantly Inherited Alzheimer, Adams, Sarah, Allegri, Ricardo, Araki, Aki, Barthelemy, Nicolas, Bechara, Jacob, Berman, Sarah, Bodge, Courtney, Brandon, Susan, Brooks, William, Brosch, Jared, Buck, Jill, Buckles, Virginia, Carter, Kathleen, Cash, Lisa, Mendez, Patricio C, Chua, Jasmin, Chui, Helena, Courtney, Laura, Day, Gregory, and DeLaCruz, Chrismary

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Biomedical Imaging, Aging, Alzheimer's Disease, Clinical Research, Neurodegenerative, Brain Disorders, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Intellectual and Developmental Disabilities (IDD), Genetics, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Aged, Humans, Middle Aged, Alzheimer Disease, Amyloid beta-Peptides, Apolipoproteins E, Biomarkers, Cross-Sectional Studies, Down Syndrome, Positron-Emission Tomography, Cerebral Cortex, Alzheimer's Biomarker Consortium-Down Syndrome, Dominantly Inherited Alzheimer Network, Neurology & Neurosurgery, Clinical sciences
Abstract

BackgroundImportant insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.MethodsIn this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.Findings192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p

Published
2023

20. Enhancing the Career Development of Rural Youth

Author

Chen, Charles P. and Doherty, Haley

Abstract

The career development experiences of rural youth are worthy of specialized attention from career counsellors. While rural youth share many commonalities with their urban counterparts, the rural experience presents distinctions that can influence their life-career decisions. To support career decision-making, career counsellors should be aware of how local economies, access to post-secondary education, and limited career exploration services shape the rural youth experience. Furthermore, counsellors must also consider the relationship between rurality and identity, and recognize how rural youth confront and negotiate this tension as they explore career options. Both theoretical and applied implications for supporting rural youth are discussed.

Published
2023
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21. Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation

Author

Yang, Kevin, Deng, Olivia, Chen, Charles, Shin, Richard, Roy, Subhro, and Van Durme, Benjamin

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

We introduce a novel setup for low-resource task-oriented semantic parsing which incorporates several constraints that may arise in real-world scenarios: (1) lack of similar datasets/models from a related domain, (2) inability to sample useful logical forms directly from a grammar, and (3) privacy requirements for unlabeled natural utterances. Our goal is to improve a low-resource semantic parser using utterances collected through user interactions. In this highly challenging but realistic setting, we investigate data augmentation approaches involving generating a set of structured canonical utterances corresponding to logical forms, before simulating corresponding natural language and filtering the resulting pairs. We find that such approaches are effective despite our restrictive setup: in a low-resource setting on the complex SMCalFlow calendaring dataset (Andreas et al., 2020), we observe 33% relative improvement over a non-data-augmented baseline in top-1 match., Comment: ACL Findings 2022

Published
2022

22. CSF proteomics identifies early changes in autosomal dominant Alzheimer’s disease

Author

Noble, James M., Day, Gregory S., Graff-Radford, Neill R., Voglein, Jonathan, Allegri, Ricardo, Mendez, Patricio Chrem, Surace, Ezequiel, Berman, Sarah B., Ikonomovic, Snezana, Nadkarni, Neelesh, Lopera, Francisco, Ramirez, Laura, Aguillon, David, Leon, Yudy, Ramos, Claudia, Alzate, Diana, Baena, Ana, Londono, Natalia, Mathias Jucker, Sonia Moreno, Laske, Christoph, Kuder-Buletta, Elke, Graber-Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ikeuchi, Takeshi, Kasuga, Kensaku, Niimi, Yoshiki, Ishii, Kenji, Senda, Michio, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Fox, Nick, Cash, Dave, Lee, Jae-Hong, Roh, Jee Hoon, Riddle, Meghan, Menard, William, Bodge, Courtney, Surti, Mustafa, Takada, Leonel Tadao, Farlow, Martin, Chhatwal, Jasmeer P., Sanchez-Gonzalez, V.J., Orozco-Barajas, Maribel, Goate, Alison, Renton, Alan, Esposito, Bianca, Karch, Celeste M., Marsh, Jacob, Cruchaga, Carlos, Fernandez, Victoria, Gordon, Brian A., Fagan, Anne M., Jerome, Gina, Herries, Elizabeth, Llibre-Guerra, Jorge, Levey, Allan I., Johnson, Erik C.B., Seyfried, Nicholas T., Schofield, Peter R., Brooks, William, Bechara, Jacob, Bateman, Randall J., McDade, Eric, Hassenstab, Jason, Perrin, Richard J., Franklin, Erin, Benzinger, Tammie L.S., Chen, Allison, Chen, Charles, Flores, Shaney, Friedrichsen, Nelly, Hantler, Nancy, Hornbeck, Russ, Jarman, Steve, Keefe, Sarah, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, McKay, Nicole, Nicklaus, Joyce, Pulizos, Christine, Wang, Qing, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily, Candela, Madison, Smith, Hunter, Hobbs, Diana, Scott, Jalen, Levin, Johannes, Xiong, Chengjie, Wang, Peter, Xu, Xiong, Li, Yan, Gremminger, Emily, Ma, Yinjiao, Bui, Ryan, Lu, Ruijin, Martins, Ralph, Sosa Ortiz, Ana Luisa, Daniels, Alisha, Courtney, Laura, Mori, Hiroshi, Supnet-Bell, Charlene, Xu, Jinbin, Ringman, John, Shen, Yuanyuan, Timsina, Jigyasha, Heo, Gyujin, Beric, Aleksandra, Ali, Muhammad, Wang, Ciyang, Yang, Chengran, Wang, Yueyao, Western, Daniel, Liu, Menghan, Gorijala, Priyanka, Budde, John, Do, Anh, Liu, Haiyan, Gordon, Brian, Llibre-Guerra, Jorge J., Joseph-Mathurin, Nelly, Maschi, Dario, Wyss-Coray, Tony, Pastor, Pau, Renton, Alan E., Surace, Ezequiel I., Alvarez, Ignacio, Ringman, John M., Allegri, Ricardo Francisco, Seyfried, Nicholas, Day, Gregg S., Wu, Qisi, Fernández, M. Victoria, Tarawneh, Rawan, Morris, John C., Ibanez, Laura, and Sung, Yun Ju

Published
2024
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23. γ-Secretase activity, clinical features, and biomarkers of autosomal dominant Alzheimer's disease: cross-sectional and longitudinal analysis of the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS)

Author

Aguillon, David, Allegri, Ricardo F., Aschenbrenner, Andrew J., Baker, Bryce, Barthelemy, Nicolas, Bechara, Jacob A., Berman, Sarah B., Brooks, William S., Cash, David M., Chen, Allison, Chrem Mendez, Patricio, Courtney, Laura, Cruchaga, Carlos, Daniels, Alisha J., Fagan, Anne M., Flores, Shaney, Fox, Nick C., Franklin, Erin, Goate, Alison M., Graber-Sultan, Susanne, Graff-Radford, Neill R., Gremminger, Emily, Herries, Elizabeth, Hofmann, Anna, Holtzman, David M., Hornbeck, Russ, Huey, Edward D., Ibanez, Laura, Ikeuchi, Takeshi, Ikonomovic, Snezana, Jackson, Kelley, Jarman, Steve, Jerome, Gina, Johnson, Erik C.B, Kasuga, Kensaku, Keefe, Sarah, Koudelis, Deborah, Kuder-Buletta, Elke, Laske, Christoph, Leon, Yudy Milena, Levey, Allan I., Li, Yan, Llibre-Guerra, Jorge J., Lopera, Francisco, Lu, Ruijin, Marsh, Jacob, Martins, Ralph, Massoumzadeh, Parinaz, Masters, Colin, McCullough, Austin, McKay, Nicole, Minton, Matthew, Mori, Hiroshi, Morris, John C., Nadkarni, Neelesh K., Nicklaus, Joyce, Niimi, Yoshiki, Noble, James M., Obermueller, Ulrike, Picarello, Danielle M., Pulizos, Christine, Ramirez, Laura, Renton, Alan E., Ringman, John, Rizzo, Jacqueline, Roedenbeck, Yvonne, Roh, Jee Hoon, Rosa-Neto, Pedro, Ryan, Natalie S., Sabaredzovic, Edita, Salloway, Stephen, Sanchez-Valle, Raquel, Scott, Jalen, Seyfried, Nicholas T., Simmons, Ashlee, Smith, Jennifer, Smith, Hunter, Stauber, Jennifer, Stout, Sarah, Supnet-Bell, Charlene, Surace, Ezequiel, Vazquez, Silvia, Vöglein, Jonathan, Wang, Guoqiao, Wang, Qing, Xu, Xiong, Xu, Jinbin, Schultz, Stephanie A, Liu, Lei, Schultz, Aaron P, Fitzpatrick, Colleen D, Levin, Raina, Bellier, Jean-Pierre, Shirzadi, Zahra, Joseph-Mathurin, Nelly, Chen, Charles D, Benzinger, Tammie L S, Day, Gregory S, Farlow, Martin R, Gordon, Brian A, Hassenstab, Jason J, Jack, Clifford R, Jr, Jucker, Mathias, Karch, Celeste M, Lee, Jae-Hong, Levin, Johannes, Perrin, Richard J, Schofield, Peter R, Xiong, Chengjie, Johnson, Keith A, McDade, Eric, Bateman, Randall J, Sperling, Reisa A, Selkoe, Dennis J, and Chhatwal, Jasmeer P

Published
2024
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25. The role of career counselling in improving the psychological and economic wellbeing of single mothers

Author

Chen, Charles P. and Edwards, Jessica

Subjects
Single mothers -- Psychological aspects -- Social aspects, Vocational guidance -- Psychological aspects, Quality of life -- Psychological aspects -- Economic aspects, Psychology and mental health
Abstract

Since the late twentieth century, there has been an increase in the number of families headed by a single female parent. Single mothers face a myriad of psychological, social, financial, and institutional challenges that impact wellbeing and career development. Career counselling efforts can provide support for single mothers' career development. In this effort, building better careers may ultimately help single mothers cope more effectively with challenges by diminishing financial strain and psychological distress while bolstering resources. The aim of this paper is to provide a theoretical overview of conditions that impact the career development of single mothers and to offer relevant counselling models and intervention strategies. Counselling strategies to improve single mothers' self-efficacy and self-concept, address role conflict and overload, and advocate for single mothers are discussed using social cognitive career theory and Super's life-span, life space theory as models for support., Author(s): Charles P. Chen [sup.1] , Jessica Edwards [sup.1] Author Affiliations: (1) https://ror.org/03dbr7087, grid.17063.33, 0000 0001 2157 2938, Counselling and Clinical Psychology Program, Department of Applied Psychology and Human Development, [...]

Published
2023
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26. Exploring the Cognitive Development of Children Born to Adolescent Mothers in South Africa

Author

Steventon Roberts, Kathryn J., Smith, Colette, Toska, Elona, Cluver, Lucie, Wittesaele, Camille, Langwenya, Nontokozo, Shenderovich, Yulia, Saal, Wylene, Jochim, Janina, Chen-Charles, Jenny, Marlow, Marguerite, and Sherr, Lorraine

Abstract

This study explores the cognitive development of children born to adolescent mothers within South Africa compared to existing reference data, and explores development by child age bands to examine relative levels of development. Cross-sectional analyses present data from 954 adolescents (10-19 years) and their first-born children (0-68 months). All adolescents completed questionnaires relating to themselves and their children, and standardized child cognitive assessments (Mullen Scales of Early Learning) were undertaken. Cognitive development scores of the sample were lower than USA reference population scores and relative performance compared to the reference population was found to decline with increasing child age. When compared to children born to adult mothers in the sub-Saharan African region, children born to adolescent mothers (human immunodeficiency virus [HIV] unexposed; n = 724) were found to have lower cognitive development scores. Findings identify critical periods of development where intervention may be required to bolster outcomes for children born to adolescent mothers.

Published
2023
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27. Career Counselling for Immigrant Students in Higher Education

Author

Chen, Charles P. and D'Cruz, Alison M.

Abstract

Professional immigrants make up a large portion of immigration to Canada, and many of these individuals pursue retraining in higher education for career transition. This article examines the career challenges faced by immigrant students and looks at their career needs through the lens of Lent, Brown and Hackett's social cognitive career theory and Krumboltz's social learning theory. "These frameworks highlight the dynamic interactions between the individual and their environment, making them especially suited to addressing the unique needs of immigrant students." This article also discusses theory-backed interventions that can be adopted by career counsellors when dealing with immigrant students.

Published
2023
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28. Counselling Approaches to Support Former Gang Members in Constructing New Careers

Author

Chen, Charles P. and Mastragostino, Emily

Abstract

Individuals with a history of gang membership face unique difficulties when transitioning out of gang participation and to alternative work. This transition can be of personal and social benefit but requires support to ensure that it is successful. Unfortunately, vocational supports for former gang members often overlook the psychological perspectives that are necessary for their career well-being. Our aim is to shed light on the common barriers former gang members face during their career transition, exploring the socio-environmental factors, identity development, and discrimination that many former gang members must overcome in a North American context. We also review major theories that promote the career well-being of former gang members and provide recommendations for counselling interventions to support their career transitions.

Published
2023
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29. Physician Perspectives on Benefits in Patient Care from UNC-Project Malawi

Author

Yang, Yi, Chen, Charles B., and Tolleson-Rinehart, Sue

Abstract

Background: The growth of academic medical centres associated with international programmes has raised questions about the benefits and harms of medical experiences abroad for medical trainees and patients. Few studies explore the potential benefits to the institution or country that send these individuals. Objective: This pilot qualitative study explores the benefits medical professionals perceive they bring back to the USA from their global health experiences abroad. Methods: Medical staff who participated in University of North Carolina (UNC)--Project Malawi and who could meet for an in-person interview from October 2016-March 2017 were recruited. Interviews were guided by an a priori semi-structured questionnaire. Each interview was transcribed and analysed by three reviewers. Results: A total of 8 out of 13 (62%) eligible potential respondents were interviewed. Participants perceived UNC-Project Malawi to benefit themselves, partnership institutions, and patients in Malawi, North Carolina, and throughout the world. After returning to UNC, participants recalled specific instances of increased diagnostic confidence (2/8) influenced by their experiences abroad. In addition, by partnering in research, participants felt that certain concepts were advanced including the syndromic management of symptomatic patients with sexually transmitted infections (1/8), the use of antiretroviral therapy to treat and prevent HIV transmission (2/8), and malaria vaccine development (1/8). Conclusion: Participants perceived that their global health experience either influenced their thought processes concerning the medical management of patients in the USA or resulted in a better understanding of research relevant to the global standard of care for specific diseases. International academic medical centre partnerships can offer rich settings for career skills development and a unique platform for collaborating on the management of clinical diseases that affect patients globally. These benefits can be maximised by establishing bi-directional curriculum goals and defining shared research agendas.

Published
2022
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31. CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer’s disease

Author

Horie, Kanta, Salvadó, Gemma, Barthélemy, Nicolas R., Janelidze, Shorena, Li, Yan, He, Yingxin, Saef, Benjamin, Chen, Charles D., Jiang, Hong, Strandberg, Olof, Pichet Binette, Alexa, Palmqvist, Sebastian, Sato, Chihiro, Sachdev, Pallavi, Koyama, Akihiko, Gordon, Brian A., Benzinger, Tammie L. S., Holtzman, David M., Morris, John C., Mattsson-Carlgren, Niklas, Stomrud, Erik, Ossenkoppele, Rik, Schindler, Suzanne E., Hansson, Oskar, and Bateman, Randall J.

Published
2023
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32. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

Author

McKay, Nicole S., Gordon, Brian A., Hornbeck, Russ C., Dincer, Aylin, Flores, Shaney, Keefe, Sarah J., Joseph-Mathurin, Nelly, Jack, Clifford R., Koeppe, Robert, Millar, Peter R., Ances, Beau M., Chen, Charles D., Daniels, Alisha, Hobbs, Diana A., Jackson, Kelley, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, Nickels, Michael L., Rahmani, Farzaneh, Swisher, Laura, Wang, Qing, Allegri, Ricardo F., Berman, Sarah B., Brickman, Adam M., Brooks, William S., Cash, David M., Chhatwal, Jasmeer P., Day, Gregory S., Farlow, Martin R., la Fougère, Christian, Fox, Nick C., Fulham, Michael, Ghetti, Bernardino, Graff-Radford, Neill, Ikeuchi, Takeshi, Klunk, William, Lee, Jae-Hong, Levin, Johannes, Martins, Ralph, Masters, Colin L., McConathy, Jonathan, Mori, Hiroshi, Noble, James M., Reischl, Gerald, Rowe, Christopher, Salloway, Stephen, Sanchez-Valle, Raquel, Schofield, Peter R., Shimada, Hiroyuki, Shoji, Mikio, Su, Yi, Suzuki, Kazushi, Vöglein, Jonathan, Yakushev, Igor, Cruchaga, Carlos, Hassenstab, Jason, Karch, Celeste, McDade, Eric, Perrin, Richard J., Xiong, Chengjie, Morris, John C., Bateman, Randall J., and Benzinger, Tammie L. S.

Published
2023
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33. Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer’s disease

Author

Chen, Charles D., McCullough, Austin, Gordon, Brian, Joseph-Mathurin, Nelly, Flores, Shaney, McKay, Nicole S., Hobbs, Diana A., Hornbeck, Russ, Fagan, Anne M., Cruchaga, Carlos, Goate, Alison M., Perrin, Richard J., Wang, Guoqiao, Li, Yan, Shi, Xinyu, Xiong, Chengjie, Pontecorvo, Michael J., Klein, Gregory, Su, Yi, Klunk, William E., Jack, Clifford, Koeppe, Robert, Snider, B. Joy, Berman, Sarah B., Roberson, Erik D., Brosch, Jared, Surti, Ghulam, Jiménez-Velázquez, Ivonne Z., Galasko, Douglas, Honig, Lawrence S., Brooks, William S., Clarnette, Roger, Wallon, David, Dubois, Bruno, Pariente, Jérémie, Pasquier, Florence, Sanchez-Valle, Raquel, Shcherbinin, Sergey, Higgins, Ixavier, Tunali, Ilke, Masters, Colin L., van Dyck, Christopher H., Masellis, Mario, Hsiung, Robin, Gauthier, Serge, Salloway, Steve, Clifford, David B., Mills, Susan, Supnet-Bell, Charlene, McDade, Eric, Bateman, Randall J., and Benzinger, Tammie L. S.

Published
2023
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36. Constrained Language Models Yield Few-Shot Semantic Parsers

Author

Shin, Richard, Lin, Christopher H., Thomson, Sam, Chen, Charles, Roy, Subhro, Platanios, Emmanouil Antonios, Pauls, Adam, Klein, Dan, Eisner, Jason, and Van Durme, Benjamin

Subjects
Computer Science - Computation and Language
Abstract

We explore the use of large pretrained language models as few-shot semantic parsers. The goal in semantic parsing is to generate a structured meaning representation given a natural language input. However, language models are trained to generate natural language. To bridge the gap, we use language models to paraphrase inputs into a controlled sublanguage resembling English that can be automatically mapped to a target meaning representation. Our results demonstrate that with only a small amount of data and very little code to convert into English-like representations, our blueprint for rapidly bootstrapping semantic parsers leads to surprisingly effective performance on multiple community tasks, greatly exceeding baseline methods also trained on the same limited data., Comment: EMNLP 2021. Code is available at https://github.com/microsoft/semantic_parsing_with_constrained_lm

Published
2021

37. Peer-Review Statements

Author

Chen, Charles, Singh, Satya Narayan, Saxena, Sandeep, Wheeb, Ali Hussein, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Chen, Charles, editor, Singh, Satya Narayan, editor, Saxena, Sandeep, editor, and Wheeb, Ali Hussein, editor

Published
2023
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46. Task-Oriented Dialogue as Dataflow Synthesis

Author

Machines, Semantic, Andreas, Jacob, Bufe, John, Burkett, David, Chen, Charles, Clausman, Josh, Crawford, Jean, Crim, Kate, DeLoach, Jordan, Dorner, Leah, Eisner, Jason, Fang, Hao, Guo, Alan, Hall, David, Hayes, Kristin, Hill, Kellie, Ho, Diana, Iwaszuk, Wendy, Jha, Smriti, Klein, Dan, Krishnamurthy, Jayant, Lanman, Theo, Liang, Percy, Lin, Christopher H, Lintsbakh, Ilya, McGovern, Andy, Nisnevich, Aleksandr, Pauls, Adam, Petters, Dmitrij, Read, Brent, Roth, Dan, Roy, Subhro, Rusak, Jesse, Short, Beth, Slomin, Div, Snyder, Ben, Striplin, Stephon, Su, Yu, Tellman, Zachary, Thomson, Sam, Vorobev, Andrei, Witoszko, Izabela, Wolfe, Jason, Wray, Abby, Zhang, Yuchen, and Zotov, Alexander

Subjects
Computer Science - Computation and Language
Abstract

We describe an approach to task-oriented dialogue in which dialogue state is represented as a dataflow graph. A dialogue agent maps each user utterance to a program that extends this graph. Programs include metacomputation operators for reference and revision that reuse dataflow fragments from previous turns. Our graph-based state enables the expression and manipulation of complex user intents, and explicit metacomputation makes these intents easier for learned models to predict. We introduce a new dataset, SMCalFlow, featuring complex dialogues about events, weather, places, and people. Experiments show that dataflow graphs and metacomputation substantially improve representability and predictability in these natural dialogues. Additional experiments on the MultiWOZ dataset show that our dataflow representation enables an otherwise off-the-shelf sequence-to-sequence model to match the best existing task-specific state tracking model. The SMCalFlow dataset and code for replicating experiments are available at https://www.microsoft.com/en-us/research/project/dataflow-based-dialogue-semantic-machines.

Published
2020
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47. Assisting Athletes Facing Career Transitions Post-Injury

Author

Chen, Charles P. and Bansal, Jotthi

Abstract

After facing a career-ending injury, athletes are often unprepared to find new occupations. With their identities and goals so deeply rooted in athletics from a young age, many athletes have not shown interest in or been educated in other fields of work. Additionally, physical and psychological trauma caused by injury and career-loss can impede the abilities to realistically perceive skills and limitations when considering new career paths. The current article identifies and discusses major issues faced by career-transitioning athletes post-injury and applies two theories, Social Cognitive Career Theory and Cochran's Narrative Theory, to career counselling methods for this population.

Published
2022
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50. Career Counselling Chinese Youth in North America

Author

Chen, Charles P.

Abstract

As a core component of culture, family influence plays an essential role on youths and individuals who grow up in families of Chinese cultural heritage in North America. This influence, overtly and covertly, shapes many aspects of these individuals' life experiences, including their work-life experiences and vocational behaviours. In this article I delineate the familial influence on work-life and careers in Chinese youths within a North American context, namely, the USA and Canada. To this end, I elaborate on the interactions between North American and Chinese cultures, family acculturation and intergeneration conflicts. Based on that, I propose ideas and career counselling strategies for Chinese North American youths struggling with negotiating between personal fulfilment and family obligation in their career development.

Published
2022
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