{"total":121,"rows":[{"id":"2105.04054","title":"Societal Biases in Language Generation: Progress and Challenges","created":"2021-05-10","cited_by_count":202,"area":null},{"id":"2310.09219","title":"\"Kelly is a Warm Person, Joseph is a Role Model\": Gender Biases in LLM-Generated Reference Letters","created":"2023-10-13","cited_by_count":199,"area":null},{"id":"2304.03738","title":"Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models","created":"2023-04-07","cited_by_count":148,"area":null},{"id":"2104.06001","title":"Gender Bias in Machine Translation","created":"2021-04-13","cited_by_count":117,"area":null},{"id":"2112.08313","title":"Measure and Improve Robustness in NLP Models: A Survey","created":"2021-12-15","cited_by_count":107,"area":null},{"id":"2107.06641","title":"Trustworthy AI: A Computational Perspective","created":"2021-07-12","cited_by_count":93,"area":null},{"id":"2112.14168","title":"A Survey on Gender Bias in Natural Language Processing","created":"2021-12-28","cited_by_count":89,"area":null},{"id":"2302.13942","title":"Inseq: An Interpretability Toolkit for Sequence Generation Models","created":"2023-02-27","cited_by_count":78,"area":null},{"id":"2411.10915","title":"Bias in Large Language Models: Origin, Evaluation, and Mitigation","created":"2024-11-16","cited_by_count":77,"area":null},{"id":"2109.03858","title":"Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation","created":"2021-09-08","cited_by_count":62,"area":null},{"id":"2205.02526","title":"Theories of \"Gender\" in NLP Bias Research","created":"2022-05-05","cited_by_count":62,"area":null},{"id":"2205.12586","title":"Perturbation Augmentation for Fairer NLP","created":"2022-05-25","cited_by_count":52,"area":null},{"id":"2104.06951","title":"Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey","created":"2021-04-14","cited_by_count":46,"area":null},{"id":"2201.09119","title":"A Causal Lens for Controllable Text Generation","created":"2022-01-22","cited_by_count":45,"area":null},{"id":"2306.07377","title":"Lost in Translation: Large Language Models in Non-English Content Analysis","created":"2023-06-12","cited_by_count":35,"area":null},{"id":"2305.10510","title":"ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages","created":"2023-05-17","cited_by_count":34,"area":null},{"id":"2210.03709","title":"Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice","created":"2022-10-07","cited_by_count":32,"area":null},{"id":"2205.12771","title":"Does Moral Code Have a Moral Code? Probing Delphi's Moral Philosophy","created":"2022-05-25","cited_by_count":31,"area":null},{"id":"2401.08495","title":"Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans","created":"2024-01-16","cited_by_count":31,"area":null},{"id":"2109.03300","title":"Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue models","created":"2021-09-07","cited_by_count":23,"area":null},{"id":"2207.02159","title":"Robustness Analysis of Video-Language Models Against Visual and Language Perturbations","created":"2022-07-05","cited_by_count":23,"area":null},{"id":"2210.06475","title":"Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models","created":"2022-10-13","cited_by_count":22,"area":null},{"id":"2301.10075","title":"Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challenges","created":"2023-01-24","cited_by_count":22,"area":null},{"id":"2104.07838","title":"Investigating Failures of Automatic Translation in the Case of Unambiguous Gender","created":"2021-04-16","cited_by_count":20,"area":null},{"id":"2109.00227","title":"Dataset for Identification of Homophobia and Transophobia in Multilingual YouTube Comments","created":"2021-09-01","cited_by_count":20,"area":null},{"id":"2310.12127","title":"A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation","created":"2023-10-18","cited_by_count":19,"area":null},{"id":"2105.02778","title":"The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification","created":"2021-05-06","cited_by_count":18,"area":null},{"id":"2107.01183","title":"Ethics Sheets for AI Tasks","created":"2021-07-02","cited_by_count":18,"area":null},{"id":"2109.05140","title":"Refocusing on Relevance: Personalization in NLG","created":"2021-09-10","cited_by_count":18,"area":null},{"id":"2303.03975","title":"GATE: A Challenge Set for Gender-Ambiguous Translation Examples","created":"2023-03-07","cited_by_count":18,"area":null},{"id":"2311.07884","title":"Fair Abstractive Summarization of Diverse Perspectives","created":"2023-11-14","cited_by_count":17,"area":null},{"id":"2402.03177","title":"CIDAR: Culturally Relevant Instruction Dataset For Arabic","created":"2024-02-05","cited_by_count":17,"area":null},{"id":"2108.10379","title":"Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation Models","created":"2021-08-23","cited_by_count":15,"area":null},{"id":"2310.17428","title":"''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text","created":"2023-10-26","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":"2311.14126","title":"Towards Auditing Large Language Models: Improving Text-based Stereotype Detection","created":"2023-11-23","cited_by_count":13,"area":null},{"id":"2403.09963","title":"Take Care of Your Prompt Bias! Investigating and Mitigating Prompt Bias in Factual Knowledge Extraction","created":"2024-03-15","cited_by_count":13,"area":null},{"id":"2405.06996","title":"Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPT","created":"2024-05-11","cited_by_count":13,"area":null},{"id":"2506.11880","title":"Addressing Bias in LLMs: Strategies and Application to Fair AI-based Recruitment","created":"2025-06-13","cited_by_count":13,"area":null},{"id":"2302.08017","title":"Preventing Discriminatory Decision-making in Evolving Data Streams","created":"2023-02-16","cited_by_count":12,"area":null},{"id":"2105.13782","title":"How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation","created":"2021-05-28","cited_by_count":11,"area":null},{"id":"2204.04440","title":"Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks","created":"2022-04-09","cited_by_count":10,"area":null},{"id":"2205.10762","title":"How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contexts","created":"2022-05-22","cited_by_count":10,"area":null},{"id":"2305.14016","title":"Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation","created":"2023-05-23","cited_by_count":10,"area":null},{"id":"2103.03598","title":"WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddings","created":"2021-03-05","cited_by_count":8,"area":null},{"id":"2107.10181","title":"Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languages","created":"2021-07-21","cited_by_count":8,"area":null},{"id":"2212.09864","title":"Synthetic Pre-Training Tasks for Neural Machine Translation","created":"2022-12-19","cited_by_count":8,"area":null},{"id":"2106.00181","title":"Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives","created":"2021-06-01","cited_by_count":7,"area":null},{"id":"2211.11678","title":"Measuring Harmful Representations in Scandinavian Language Models","created":"2022-11-21","cited_by_count":7,"area":null},{"id":"2212.01700","title":"Towards Robust NLG Bias Evaluation with Syntactically-diverse Prompts","created":"2022-12-03","cited_by_count":7,"area":null},{"id":"2212.11672","title":"Trustworthy Social Bias Measurement","created":"2022-12-20","cited_by_count":7,"area":null},{"id":"2303.01692","title":"Travel Demand Forecasting: A Fair AI Approach","created":"2023-03-03","cited_by_count":7,"area":null},{"id":"2306.04573","title":"Gender, names and other mysteries: Towards the ambiguous for gender-inclusive translation","created":"2023-06-07","cited_by_count":7,"area":null},{"id":"2104.02532","title":"End-To-End Bias Mitigation: Removing Gender Bias in Deep Learning","created":"2021-04-06","cited_by_count":6,"area":null},{"id":"2302.02038","title":"Rating Sentiment Analysis Systems for Bias through a Causal Lens","created":"2023-02-04","cited_by_count":6,"area":null},{"id":"2302.09079","title":"Advances in Automatically Rating the Trustworthiness of Text Processing Services","created":"2023-02-04","cited_by_count":6,"area":null},{"id":"2307.10057","title":"Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges","created":"2023-07-14","cited_by_count":6,"area":null},{"id":"2104.07695","title":"Improving Gender Translation Accuracy with Filtered Self-Training","created":"2021-04-15","cited_by_count":5,"area":null},{"id":"2110.01330","title":"InfiniteForm: A synthetic, minimal bias dataset for fitness applications","created":"2021-10-04","cited_by_count":5,"area":null},{"id":"2302.05508","title":"FairPy: A Toolkit for Evaluation of Prediction Biases and their Mitigation in Large Language Models","created":"2023-02-10","cited_by_count":5,"area":null},{"id":"2306.07152","title":"Measuring Sentiment Bias in Machine Translation","created":"2023-06-12","cited_by_count":5,"area":null},{"id":"2412.21052","title":"Towards Effective Discrimination Testing for Generative AI","created":"2024-12-30","cited_by_count":5,"area":null},{"id":"2503.04372","title":"Assumed Identities: Quantifying Gender Bias in Machine Translation of Gender-Ambiguous Occupational Terms","created":"2025-03-06","cited_by_count":5,"area":null},{"id":"2511.21517","title":"Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation","created":"2025-11-26","cited_by_count":5,"area":null},{"id":"2104.05700","title":"Macro-Average: Rare Types Are Important Too","created":"2021-04-12","cited_by_count":4,"area":null},{"id":"2108.06217","title":"Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice","created":"2021-08-11","cited_by_count":4,"area":null},{"id":"2211.13709","title":"Undesirable Biases in NLP: Addressing Challenges of Measurement","created":"2022-11-24","cited_by_count":4,"area":null},{"id":"2304.13557","title":"\"I'm\" Lost in Translation: Pronoun Missteps in Crowdsourced Data Sets","created":"2023-04-22","cited_by_count":4,"area":null},{"id":"2311.03767","title":"Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine Translation","created":"2023-11-07","cited_by_count":4,"area":null},{"id":"2401.10016","title":"Gender Bias in Machine Translation and The Era of Large Language Models","created":"2024-01-18","cited_by_count":4,"area":null},{"id":"2401.12985","title":"The Effect of Human v/s Synthetic Test Data and Round-tripping on Assessment of Sentiment Analysis Systems for Bias","created":"2024-01-15","cited_by_count":4,"area":null},{"id":"2402.14277","title":"GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages","created":"2024-02-22","cited_by_count":4,"area":null},{"id":"2406.01757","title":"Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities","created":"2024-06-03","cited_by_count":4,"area":null},{"id":"2304.05764","title":"Measuring Normative and Descriptive Biases in Language Models Using Census Data","created":"2023-04-12","cited_by_count":3,"area":null},{"id":"2307.00472","title":"Equal Confusion Fairness: Measuring Group-Based Disparities in Automated Decision Systems","created":"2023-07-02","cited_by_count":3,"area":null},{"id":"2308.16871","title":"The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages","created":"2023-08-31","cited_by_count":3,"area":null},{"id":"2309.03175","title":"Gender-specific Machine Translation with Large Language Models","created":"2023-09-06","cited_by_count":3,"area":null},{"id":"2310.14610","title":"That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2404.01768","title":"Stereotype Detection in LLMs: A Multiclass, Explainable, and Benchmark-Driven Approach","created":"2024-04-02","cited_by_count":3,"area":null},{"id":"2408.02948","title":"Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicality","created":"2024-08-06","cited_by_count":3,"area":null},{"id":"2506.09558","title":"Gender Bias in English-to-Greek Machine Translation","created":"2025-06-11","cited_by_count":3,"area":null},{"id":"2109.12105","title":"Faithful Target Attribute Prediction in Neural Machine Translation","created":"2021-09-24","cited_by_count":2,"area":null},{"id":"2203.10264","title":"Assessing Gender Bias in Predictive Algorithms using eXplainable AI","created":"2022-03-19","cited_by_count":2,"area":null},{"id":"2205.07774","title":"Gradient-based Counterfactual Explanations using Tractable Probabilistic Models","created":"2022-05-16","cited_by_count":2,"area":null},{"id":"2209.02793","title":"\"Es geht um Respekt, nicht um Technologie\": Erkenntnisse aus einem Interessensgruppen-\\\"ubergreifenden Workshop zu genderfairer Sprache und Sprachtechnologie","created":"2022-09-06","cited_by_count":2,"area":null},{"id":"2305.18320","title":"Cognitive network science reveals bias in GPT-3, ChatGPT, and GPT-4 mirroring math anxiety in high-school students","created":"2023-05-22","cited_by_count":2,"area":null},{"id":"2306.05882","title":"Good, but not always Fair: An Evaluation of Gender Bias for three commercial Machine Translation Systems","created":"2023-06-09","cited_by_count":2,"area":null},{"id":"2306.10530","title":"Gender Bias in Transformer Models: A comprehensive survey","created":"2023-06-18","cited_by_count":2,"area":null},{"id":"2307.08624","title":"National Origin Discrimination in Deep-learning-powered Automated Resume Screening","created":"2023-07-13","cited_by_count":2,"area":null},{"id":"2309.08121","title":"\"I'm Not Confident in Debiasing AI Systems Since I Know Too Little\": Teaching AI Creators About Gender Bias Through Hands-on Tutorials","created":"2023-09-15","cited_by_count":2,"area":null},{"id":"2310.15114","title":"How To Build Competitive Multi-gender Speech Translation Models For Controlling Speaker Gender Translation","created":"2023-10-23","cited_by_count":2,"area":null},{"id":"2311.17301","title":"Language Models: A Guide for the Perplexed","created":"2023-11-29","cited_by_count":2,"area":null},{"id":"2503.21393","title":"An evaluation of LLMs and Google Translate for translation of selected Indian languages via sentiment and semantic analyses","created":"2025-03-27","cited_by_count":2,"area":null},{"id":"2509.13803","title":"Measuring Gender Bias in Job Title Matching for Grammatical Gender Languages","created":"2025-09-17","cited_by_count":2,"area":null},{"id":"2603.26539","title":"How Open Must Language Models be to Enable Reliable Scientific Inference?","created":"2026-03-27","cited_by_count":2,"area":null},{"id":"2112.09326","title":"Cinderella's shoe won't fit Soundarya: An audit of facial processing tools on Indian faces","created":"2021-12-17","cited_by_count":1,"area":null},{"id":"2202.12568","title":"Screening Gender Transfer in Neural Machine Translation","created":"2022-02-25","cited_by_count":1,"area":null},{"id":"2207.08104","title":"A Multibias-mitigated and Sentiment Knowledge Enriched Transformer for Debiasing in Multimodal Conversational Emotion Recognition","created":"2022-07-17","cited_by_count":1,"area":null},{"id":"2212.06574","title":"Artificial intelligence technologies to support research assessment: A review","created":"2022-12-11","cited_by_count":1,"area":null},{"id":"2301.08998","title":"Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings","created":"2023-01-21","cited_by_count":1,"area":null}],"next_cursor":"100"}