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Search query suggestions affect users' interactions with search engines, which then influences the information they encounter. Thus, bias in search query suggestions can lead to exposure to biased search results and can impact opinion formation. This is especially critical in the political domain. Detecting and quantifying bias in web search engines is difficult due to its topic dependency, complexity, and subjectivity. The lack of context and phrasality of query suggestions emphasizes this problem. In a multi-step approach, we combine the benefits of large language models, pairwise comparison, and Elo-based scoring to identify and quantify bias in English search query suggestions. We apply our approach to the U.S. political news domain and compare bias in Google and Bing.

In this paper, we propose LiOn-XA, an unsupervised domain adaptation (UDA) approach that combines LiDAR-Only Cross-Modal (X) learning with Adversarial training for 3D LiDAR point cloud semantic segmentation to bridge the domain gap arising from environmental and sensor setup changes. Unlike existing works that exploit multiple data modalities like point clouds and RGB image data, we address UDA in scenarios where RGB images might not be available and show that two distinct LiDAR data representations can learn from each other for UDA. More specifically, we leverage 3D voxelized point clouds to preserve important geometric structure in combination with 2D projection-based range images that provide information such as object orientations or surfaces. To further align the feature space between both domains, we apply adversarial training using both features and predictions of both 2D and 3D neural networks. Our experiments on 3 real-to-real adaptation scenarios demonstrate the effectiveness of our approach, achieving new state-of-the-art performance when compared to previous uni- and multi-model UDA methods. Our source code is publicly available at https://github.com/JensLe97/lion-xa., Comment: Preprint, Paper has been accepted at IROS2024

Archives of libraries contain many materials, which have not yet been made available to the public. The prioritization of which content to provide and especially how to design effective access paths depend on potential users' needs. As a case study we interviewed researchers working on topics related to one German philosopher to map out their information interaction workflow. Additionally, we deeply analyze study participants' requirements for a digital library system. Moreover, we discuss how existing methods may meet their requirements and which implications these methods may have in a practical digital library setting, e.g., computational costs and hallucinations. In brief, this paper contributes the findings of our digital humanities case study resulting in system requirements., Comment: Technical Report of our accepted JCDL 2024 Poster, 6 pages

This paper is a report of the Workshop on Simulations for Information Access (Sim4IA) workshop at SIGIR 2024. The workshop had two keynotes, a panel discussion, nine lightning talks, and two breakout sessions. Key takeaways were user simulation's importance in academia and industry, the possible bridging of online and offline evaluation, and the issues of organizing a companion shared task around user simulations for information access. We report on how we organized the workshop, provide a brief overview of what happened at the workshop, and summarize the main topics and findings of the workshop and future work., Comment: Preprint of a SIGIR Forum submission for Vol. 58 No. 2 - December 2024

Building on the foundations of our previous work, this paper introduces Arena 4.0, a significant advancement over Arena 3.0, Arena-Bench, Arena 1.0, and Arena 2.0. Arena 4.0 offers three key novel contributions: (1) a generative-model-based world and scenario generation approach that utilizes large language models (LLMs) and diffusion models to dynamically generate complex, human-centric environments from text prompts or 2D floorplans, useful for the development and benchmarking of social navigation strategies; (2) a comprehensive 3D model database, extendable with additional 3D assets that are semantically linked and annotated for dynamic spawning and arrangement within 3D worlds; and (3) a complete migration to ROS 2, enabling compatibility with modern hardware and enhanced functionalities for improved navigation, usability, and easier deployment on real robots. We evaluated the platform's performance through a comprehensive user study, demonstrating significant improvements in usability and efficiency compared to previous versions. Arena 4.0 is openly available at https://github.com/Arena-Rosnav., Comment: 7 pages, 7 figures

In this short note we review results on equilibrium shapes of minimizers to the sessile drop problem. More precisely, we study the Winterbottom problem and prove that the Winterbottom shape is indeed optimal. The arguments presented here are based on relaxation and the (anisotropic) isoperimetric inequality.

Blockchains were originally designed as closed execution environments and lack the ability to communicate directly with external systems. To overcome this limitation, many blockchains employ relayers, external applications capable of transporting data between different blockchains. Typically, the process of relaying data is permissionless and multiple independent relayers work concurrently to transport the same information between two blockchains. While this model increases the reliability of data delivery by providing redundancy, it also introduces challenges that have not been previously discussed. In this work, we bridge this gap by discussing the shortcomings of permissionless cross-chain relaying systems and identifying three issues that adversely impact their performance, scalability and security. We take the first step towards addressing issues that hinder performance and scalability by proposing a novel protocol to enable coordination among independent relayers. Additionally, we provide an in-depth discussion about the trade-offs associated with the design of relayer coordination protocols for permissionless settings. Through this work we provide a foundation for improving cross-chain relaying services.

Hodge theory associates to a smooth projective variety over $\mathbb{C}$ a piece of linear algebra information, called a $\mathbb{Q}$-Hodge structure. Conversely, it is a natural question which abstract $\mathbb{Q}$-Hodge structures arise from the cohomology of a smooth projective complex variety, or more generally, from a pure motive over $\mathbb{C}$. By a classical argument involving Griffiths transversality and a Baire category argument, it is well known that there are many Hodge structures which do not come from geometry in this sense. However, the argument is not constructive, and does not seem to give a criterion to decide whether a given Hodge structure comes from geometry. We formulate an intrinsic condition on a $\mathbb{Q}$-Hodge structure that we expect to be satisfied for all Hodge structures coming from geometry. We prove that this expectation follows from the conjunction of two fundamental conjectures in Hodge theory and transcendence theory: the conjecture that Hodge cycles are motivated and Andr\'e's generalized Grothendieck period conjecture. By doing so, we exhibit explicit examples of $\mathbb{Q}$-Hodge structures which should not come from geometry., Comment: Comments welcome!

Digital libraries oftentimes provide access to historical newspaper archives via keyword-based search. Historical figures and their roles are particularly interesting cognitive access points in historical research. Structuring and clustering news articles would allow more sophisticated access for users to explore such information. However, real-world limitations such as the lack of training data, licensing restrictions and non-English text with OCR errors make the composition of such a system difficult and cost-intensive in practice. In this work we tackle these issues with the showcase of the National Library of the Netherlands by introducing a role-based interface that structures news articles on historical persons. In-depth, component-wise evaluations and interviews with domain experts highlighted our prototype's effectiveness and appropriateness for a real-world digital library collection., Comment: TPDL2023, Full Paper, 16 pages

Reading levels are highly individual and can depend on a text's language, a person's cognitive abilities, or knowledge on a topic. Text simplification is the task of rephrasing a text to better cater to the abilities of a specific target reader group. Simplification of scientific abstracts helps non-experts to access the core information by bypassing formulations that require domain or expert knowledge. This is especially relevant for, e.g., cancer patients reading about novel treatment options. The SimpleText lab hosts the simplification of scientific abstracts for non-experts (Task 3) to advance this field. We contribute three runs employing out-of-the-box summarization models (two based on T5, one based on PEGASUS) and one run using ChatGPT with complex phrase identification., Comment: Paper accepted at SimpleText@CLEF'23, 12 pages, 1 Figure, 4 Tables