{"total":58,"rows":[{"id":"2106.13219","title":"Towards Understanding and Mitigating Social Biases in Language Models","created":"2021-06-24","cited_by_count":296,"area":null},{"id":"2105.04054","title":"Societal Biases in Language Generation: Progress and Challenges","created":"2021-05-10","cited_by_count":202,"area":null},{"id":"2104.06001","title":"Gender Bias in Machine Translation","created":"2021-04-13","cited_by_count":117,"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":"2205.02526","title":"Theories of \"Gender\" in NLP Bias Research","created":"2022-05-05","cited_by_count":62,"area":null},{"id":"2403.03121","title":"Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution","created":"2024-03-05","cited_by_count":40,"area":null},{"id":"2306.08158","title":"Sociodemographic Bias in Language Models: A Survey and Forward Path","created":"2023-06-13","cited_by_count":28,"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":"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":"2406.08824","title":"LLM-Driven Robots Risk Enacting Discrimination, Violence, and Unlawful Actions","created":"2024-06-13","cited_by_count":22,"area":null},{"id":"2310.05294","title":"Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus","created":"2023-10-08","cited_by_count":20,"area":null},{"id":"2106.08680","title":"Evaluating Gender Bias in Hindi-English Machine Translation","created":"2021-06-16","cited_by_count":19,"area":null},{"id":"2305.16051","title":"What about em? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns","created":"2023-05-25","cited_by_count":19,"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":"2302.12578","title":"Fairness in Language Models Beyond English: Gaps and Challenges","created":"2023-02-24","cited_by_count":16,"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":"2309.01826","title":"One Wide Feedforward is All You Need","created":"2023-09-04","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":"2410.00545","title":"What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Study","created":"2024-10-01","cited_by_count":15,"area":null},{"id":"2308.12539","title":"CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Bias","created":"2023-08-24","cited_by_count":14,"area":null},{"id":"2305.02665","title":"Learning Language-Specific Layers for Multilingual Machine Translation","created":"2023-05-04","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":"2402.06041","title":"A Prompt Response to the Demand for Automatic Gender-Neutral Translation","created":"2024-02-08","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":"2304.05783","title":"Measuring Gender Bias in West Slavic Language Models","created":"2023-04-12","cited_by_count":10,"area":null},{"id":"2410.10995","title":"Watching the Watchers: Exposing Gender Disparities in Machine Translation Quality Estimation","created":"2024-10-14","cited_by_count":10,"area":null},{"id":"2211.11678","title":"Measuring Harmful Representations in Scandinavian Language Models","created":"2022-11-21","cited_by_count":7,"area":null},{"id":"2310.19345","title":"Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INES","created":"2023-10-30","cited_by_count":6,"area":null},{"id":"2405.08238","title":"Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT","created":"2024-05-13","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":"2401.06935","title":"MiTTenS: A Dataset for Evaluating Gender Mistranslation","created":"2024-01-13","cited_by_count":5,"area":null},{"id":"2405.06687","title":"Hire Me or Not? Examining Language Model's Behavior with Occupation Attributes","created":"2024-05-06","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":"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":"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":"2506.09558","title":"Gender Bias in English-to-Greek Machine Translation","created":"2025-06-11","cited_by_count":3,"area":null},{"id":"2506.15676","title":"Gender-Neutral Machine Translation Strategies in Practice","created":"2025-06-18","cited_by_count":3,"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":"2405.00134","title":"Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns","created":"2024-04-30","cited_by_count":2,"area":null},{"id":"2507.18338","title":"Uncertainty Quantification for Evaluating Machine Translation Bias","created":"2025-07-24","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":"2512.08440","title":"What Triggers my Model? Contrastive Explanations Inform Gender Choices by Translation Models","created":"2025-12-09","cited_by_count":2,"area":null},{"id":"2306.09752","title":"Politeness Stereotypes and Attack Vectors: Gender Stereotypes in Japanese and Korean Language Models","created":"2023-06-16","cited_by_count":1,"area":null},{"id":"2407.16266","title":"Beyond Binary Gender: Evaluating Gender-Inclusive Machine Translation with Ambiguous Attitude Words","created":"2024-07-23","cited_by_count":1,"area":null},{"id":"2506.01998","title":"Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents","created":"2025-05-20","cited_by_count":1,"area":null},{"id":"2111.11159","title":"Investigating Cross-Linguistic Gender Bias in Hindi-English Across Domains","created":"2021-11-22","cited_by_count":0,"area":null},{"id":"2305.12143","title":"Learning Horn Envelopes via Queries from Large Language Models","created":"2023-05-20","cited_by_count":0,"area":null},{"id":"2310.10571","title":"Emerging Challenges in Personalized Medicine: Assessing Demographic Effects on Biomedical Question Answering Systems","created":"2023-10-16","cited_by_count":0,"area":null},{"id":"2312.03710","title":"Don't Overlook the Grammatical Gender: Bias Evaluation for Hindi-English Machine Translation","created":"2023-11-11","cited_by_count":0,"area":null},{"id":"2401.13165","title":"Misgendering and Assuming Gender in Machine Translation when Working with Low-Resource Languages","created":"2024-01-24","cited_by_count":0,"area":null},{"id":"2407.15154","title":"Fine-grained Gender Control in Machine Translation with Large Language Models","created":"2024-07-21","cited_by_count":0,"area":null},{"id":"2603.17962","title":"ConGA: Guidelines for Contextual Gender Annotation. A Framework for Annotating Gender in Machine Translation","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2610.14769","title":"Who Receives Respect? A Counterfactual Benchmark for Honorific Allocation Bias in Bengali","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}