{"total":42,"rows":[{"id":"2411.10915","title":"Bias in Large Language Models: Origin, Evaluation, and Mitigation","created":"2024-11-16","cited_by_count":77,"area":null},{"id":"2404.01349","title":"Fairness in Large Language Models: A Taxonomic Survey","created":"2024-03-31","cited_by_count":58,"area":null},{"id":"2402.17649","title":"Beyond prompt brittleness: Evaluating the reliability and consistency of political worldviews in LLMs","created":"2024-02-27","cited_by_count":55,"area":null},{"id":"2407.20371","title":"Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval","created":"2024-07-29","cited_by_count":51,"area":null},{"id":"2402.16382","title":"Immunization against harmful fine-tuning attacks","created":"2024-02-26","cited_by_count":35,"area":null},{"id":"2406.07243","title":"MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs","created":"2024-06-11","cited_by_count":35,"area":null},{"id":"2407.04965","title":"Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression","created":"2024-07-06","cited_by_count":33,"area":null},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2502.01926","title":"Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs","created":"2025-02-04","cited_by_count":20,"area":null},{"id":"2404.12020","title":"Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering","created":"2024-04-18","cited_by_count":18,"area":null},{"id":"2406.14230","title":"Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing","created":"2024-06-20","cited_by_count":17,"area":null},{"id":"2503.06987","title":"Social Bias Benchmark for Generation: A Comparison of Generation and QA-Based Evaluations","created":"2025-03-10","cited_by_count":16,"area":null},{"id":"2406.04755","title":"LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses","created":"2024-06-07","cited_by_count":15,"area":null},{"id":"2406.04064","title":"Ask LLMs Directly, \"What shapes your bias?\": Measuring Social Bias in Large Language Models","created":"2024-06-06","cited_by_count":14,"area":null},{"id":"2405.14555","title":"Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models","created":"2024-05-23","cited_by_count":10,"area":null},{"id":"2407.11733","title":"How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studies","created":"2024-07-16","cited_by_count":10,"area":null},{"id":"2412.06134","title":"Evaluating and Mitigating Social Bias for Large Language Models in Open-ended Settings","created":"2024-12-09","cited_by_count":10,"area":null},{"id":"2405.17512","title":"On Fairness of Low-Rank Adaptation of Large Models","created":"2024-05-27","cited_by_count":9,"area":null},{"id":"2603.21524","title":"CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs","created":"2026-03-23","cited_by_count":9,"area":null},{"id":"2406.08183","title":"Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Prediction","created":"2024-06-12","cited_by_count":6,"area":null},{"id":"2505.18545","title":"B-score: Detecting biases in large language models using response history","created":"2025-05-24","cited_by_count":6,"area":null},{"id":"2505.04673","title":"REVEAL: Multi-turn Evaluation of Image-Input Harms for Vision LLM","created":"2025-05-07","cited_by_count":5,"area":null},{"id":"2506.11111","title":"Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions","created":"2025-06-08","cited_by_count":5,"area":null},{"id":"2312.15478","title":"A Group Fairness Lens for Large Language Models","created":"2023-12-24","cited_by_count":4,"area":null},{"id":"2410.05401","title":"Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation","created":"2024-10-07","cited_by_count":4,"area":null},{"id":"2504.03520","title":"Neutralizing the Narrative: AI-Powered Debiasing of Online News Articles","created":"2025-04-04","cited_by_count":4,"area":null},{"id":"2505.13531","title":"AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference","created":"2025-05-18","cited_by_count":4,"area":null},{"id":"2406.04220","title":"BEADs: Bias Evaluation Across Domains","created":"2024-06-06","cited_by_count":3,"area":null},{"id":"2406.13556","title":"Evaluating Short-Term Temporal Fluctuations of Social Biases in Social Media Data and Masked Language Models","created":"2024-06-19","cited_by_count":3,"area":null},{"id":"2409.13843","title":"STOP! Benchmarking Large Language Models with Sensitivity Testing on Offensive Progressions","created":"2024-09-20","cited_by_count":2,"area":null},{"id":"2504.14212","title":"Bias Analysis and Mitigation through Protected Attribute Detection and Regard Classification","created":"2025-04-19","cited_by_count":2,"area":null},{"id":"2505.10013","title":"DIF: A Framework for Benchmarking and Verifying Implicit Bias in LLMs","created":"2025-05-15","cited_by_count":2,"area":null},{"id":"2505.17131","title":"Relative Bias: A Comparative Framework for Quantifying Bias in LLMs","created":"2025-05-22","cited_by_count":2,"area":null},{"id":"2601.00996","title":"VEAT Quantifies Implicit Associations in Text-to-Video Generator Sora and Reveals Challenges in Bias Mitigation","created":"2026-01-02","cited_by_count":2,"area":null},{"id":"2410.14894","title":"Soft-Label Integration for Robust Toxicity Classification","created":"2024-10-18","cited_by_count":1,"area":null},{"id":"2503.16444","title":"Conversational Explanations: Discussing Explainable AI with Non-AI Experts","created":"2025-02-16","cited_by_count":1,"area":null},{"id":"2506.22481","title":"Theories of \"Sexuality\" in Natural Language Processing Bias Research","created":"2025-06-22","cited_by_count":1,"area":null},{"id":"2601.04474","title":"Computational Compliance for AI Regulation: Blueprint for a New Research Domain","created":"2026-01-08","cited_by_count":1,"area":null},{"id":"2412.01711","title":"Towards Resource Efficient and Interpretable Bias Mitigation in Large Language Models","created":"2024-12-02","cited_by_count":0,"area":null},{"id":"2503.16674","title":"Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Markets","created":"2025-03-20","cited_by_count":0,"area":null},{"id":"2512.10734","title":"Textual Data Bias Detection and Mitigation -- An Extensible Pipeline with Experimental Evaluation","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2512.15792","title":"A Multifaceted Analysis of Social Biases in Large Language Models","created":"2025-12-16","cited_by_count":0,"area":null}],"next_cursor":null}