228 results on '"Qiaozhu Mei"'
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2. PRewrite: Prompt Rewriting with Reinforcement Learning.
3. Bridging the Preference Gap between Retrievers and LLMs.
4. Learning to Rewrite Prompts for Personalized Text Generation.
5. Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss.
6. Emoji Promotes Developer Participation and Issue Resolution on GitHub.
7. The Second Workshop on Large Language Models for Individuals, Groups, and Society.
8. PM2.5 forecasting under distribution shift: A graph learning approach.
9. Adoption of Recurrent Innovations: A Large-Scale Case Study on Mobile App Updates.
10. The First Workshop on AI Behavioral Science.
11. WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society.
12. Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach.
13. Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses.
14. Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?
15. PRewrite: Prompt Rewriting with Reinforcement Learning.
16. Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions.
17. Bridging the Preference Gap between Retrievers and LLMs.
18. Unlocking the 'Why' of Buying: Introducing a New Dataset and Benchmark for Purchase Reason and Post-Purchase Experience.
19. MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows.
20. A Prompt Log Analysis of Text-to-Image Generation Systems.
21. Team Resilience under Shock: An Empirical Analysis of GitHub Repositories during Early COVID-19 Pandemic.
22. Putting Teams into the Gig Economy: A Field Experiment at a Ride-Sharing Platform.
23. Adapting Pre-trained Language Models to Low-Resource Text Simplification: The Path Matters.
24. Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem.
25. Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling.
26. How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules.
27. A Metadata-Driven Approach to Understand Graph Neural Networks.
28. The 3rd Workshop on Graph Learning Benchmarks (GLB 2023).
29. SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks.
30. Systematic Analysis of Fine-Grained Mobility Prediction With On-Device Contextual Data.
31. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
32. Team Resilience under Shock: An Empirical Analysis of GitHub Repositories during Early COVID-19 Pandemic.
33. A Prompt Log Analysis of Text-to-Image Generation Systems.
34. Perspectives on Privacy in the Post-Roe Era: A Mixed-Methods of Machine Learning and Qualitative Analyses of Tweets.
35. A Metadata-Driven Approach to Understand Graph Neural Networks.
36. Emoji Promotes Developer Participation and Issue Resolution on GitHub.
37. Automatic Prompt Rewriting for Personalized Text Generation.
38. Can LLMs Effectively Leverage Graph Structural Information: When and Why.
39. Ranking & Reweighting Improves Group Distributional Robustness.
40. Automated Evaluation of Personalized Text Generation using Large Language Models.
41. Teach LLMs to Personalize - An Approach inspired by Writing Education.
42. A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?
43. Meta Semantic Template for Evaluation of Large Language Models.
44. Partition-Based Active Learning for Graph Neural Networks.
45. Subgroup Generalization and Fairness of Graph Neural Networks.
46. DeepRec: On-device Deep Learning for Privacy-Preserving Sequential Recommendation in Mobile Commerce.
47. Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model.
48. Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification.
49. UMSIForeseer at SemEval-2020 Task 11: Propaganda Detection by Fine-Tuning BERT with Resampling and Ensemble Learning.
50. Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy.
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