{"total":131,"rows":[{"id":"2112.04359","title":"Ethical and social risks of harm from Language Models","created":"2021-12-08","cited_by_count":966,"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":"2402.17944","title":"Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey","created":"2024-02-27","cited_by_count":159,"area":null},{"id":"2106.03521","title":"RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models","created":"2021-06-07","cited_by_count":149,"area":null},{"id":"2306.10070","title":"Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health","created":"2023-06-15","cited_by_count":118,"area":null},{"id":"2104.06001","title":"Gender Bias in Machine Translation","created":"2021-04-13","cited_by_count":117,"area":null},{"id":"2308.10149","title":"A Survey on Fairness in Large Language Models","created":"2023-08-20","cited_by_count":95,"area":null},{"id":"2107.06641","title":"Trustworthy AI: A Computational Perspective","created":"2021-07-12","cited_by_count":93,"area":null},{"id":"2104.08646","title":"Competency Problems: On Finding and Removing Artifacts in Language Data","created":"2021-04-17","cited_by_count":91,"area":null},{"id":"2109.05704","title":"Mitigating Language-Dependent Ethnic Bias in BERT","created":"2021-09-13","cited_by_count":87,"area":null},{"id":"2106.14574","title":"Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics","created":"2021-06-28","cited_by_count":83,"area":null},{"id":"2107.03451","title":"Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling","created":"2021-07-07","cited_by_count":78,"area":null},{"id":"2106.11410","title":"A Survey of Race, Racism, and Anti-Racism in NLP","created":"2021-06-21","cited_by_count":75,"area":null},{"id":"2202.00126","title":"Handling Bias in Toxic Speech Detection: A Survey","created":"2022-01-26","cited_by_count":61,"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":"2312.01261","title":"TIBET: Identifying and Evaluating Biases in Text-to-Image Generative Models","created":"2023-12-03","cited_by_count":52,"area":null},{"id":"2206.09917","title":"Multilingual HateCheck: Functional Tests for Multilingual Hate Speech Detection Models","created":"2022-06-20","cited_by_count":51,"area":null},{"id":"2206.08325","title":"Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models","created":"2022-06-16","cited_by_count":49,"area":null},{"id":"2202.11923","title":"Welcome to the Modern World of Pronouns: Identity-Inclusive Natural Language Processing beyond Gender","created":"2022-02-24","cited_by_count":47,"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":"2101.11974","title":"Disembodied Machine Learning: On the Illusion of Objectivity in NLP","created":"2021-01-28","cited_by_count":37,"area":null},{"id":"2305.14291","title":"Evaluation of African American Language Bias in Natural Language Generation","created":"2023-05-23","cited_by_count":36,"area":null},{"id":"2209.03463","title":"Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots","created":"2022-09-07","cited_by_count":33,"area":null},{"id":"2104.07429","title":"First the worst: Finding better gender translations during beam search","created":"2021-04-15","cited_by_count":29,"area":null},{"id":"2304.10153","title":"On the Independence of Association Bias and Empirical Fairness in Language Models","created":"2023-04-20","cited_by_count":29,"area":null},{"id":"2306.01183","title":"Systematic Evaluation of GPT-3 for Zero-Shot Personality Estimation","created":"2023-06-01","cited_by_count":29,"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":"2105.02590","title":"Reliability Testing for Natural Language Processing Systems","created":"2021-05-06","cited_by_count":25,"area":null},{"id":"2405.06563","title":"What Can Natural Language Processing Do for Peer Review?","created":"2024-05-10","cited_by_count":25,"area":null},{"id":"2109.02071","title":"End-to-End Self-Debiasing Framework for Robust NLU Training","created":"2021-09-05","cited_by_count":24,"area":null},{"id":"2203.09866","title":"Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation","created":"2022-03-18","cited_by_count":23,"area":null},{"id":"2211.05617","title":"Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey","created":"2022-11-10","cited_by_count":22,"area":null},{"id":"2202.12690","title":"On Modality Bias Recognition and Reduction","created":"2022-02-25","cited_by_count":20,"area":null},{"id":"2206.03945","title":"Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models","created":"2022-06-08","cited_by_count":20,"area":null},{"id":"2107.11610","title":"Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition","created":"2021-07-24","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":"2109.05140","title":"Refocusing on Relevance: Personalization in NLG","created":"2021-09-10","cited_by_count":18,"area":null},{"id":"2203.07523","title":"Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense Embeddings","created":"2022-03-14","cited_by_count":18,"area":null},{"id":"2204.04026","title":"Fair and Argumentative Language Modeling for Computational Argumentation","created":"2022-04-08","cited_by_count":18,"area":null},{"id":"2402.02675","title":"Verifiable evaluations of machine learning models using zkSNARKs","created":"2024-02-05","cited_by_count":16,"area":null},{"id":"2507.13541","title":"PrefPalette: Personalized Preference Modeling with Latent Attributes","created":"2025-07-17","cited_by_count":16,"area":null},{"id":"2105.03484","title":"Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality","created":"2021-05-07","cited_by_count":15,"area":null},{"id":"2205.00328","title":"HateCheckHIn: Evaluating Hindi Hate Speech Detection Models","created":"2022-04-30","cited_by_count":15,"area":null},{"id":"2302.06488","title":"Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data Diversity","created":"2023-02-13","cited_by_count":15,"area":null},{"id":"2109.08613","title":"Adversarial Scrubbing of Demographic Information for Text Classification","created":"2021-09-17","cited_by_count":14,"area":null},{"id":"2110.08038","title":"Toward Annotator Group Bias in Crowdsourcing","created":"2021-10-08","cited_by_count":14,"area":null},{"id":"2206.01134","title":"Language and Culture Internalisation for Human-Like Autotelic AI","created":"2022-06-02","cited_by_count":14,"area":null},{"id":"2311.10395","title":"Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads","created":"2023-11-17","cited_by_count":14,"area":null},{"id":"2405.02411","title":"The Call for Socially Aware Language Technologies","created":"2024-05-03","cited_by_count":13,"area":null},{"id":"2407.09241","title":"The Sociolinguistic Foundations of Language Modeling","created":"2024-07-12","cited_by_count":13,"area":null},{"id":"2104.00358","title":"Nine Potential Pitfalls when Designing Human-AI Co-Creative Systems","created":"2021-04-01","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":"2201.00768","title":"Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions","created":"2022-01-03","cited_by_count":11,"area":null},{"id":"2312.07751","title":"Large Human Language Models: A Need and the Challenges","created":"2023-11-09","cited_by_count":11,"area":null},{"id":"2407.18454","title":"Fairness Definitions in Language Models Explained","created":"2024-07-26","cited_by_count":11,"area":null},{"id":"2210.07873","title":"A Second Wave of UD Hebrew Treebanking and Cross-Domain Parsing","created":"2022-10-14","cited_by_count":10,"area":null},{"id":"2409.18454","title":"Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications","created":"2024-09-27","cited_by_count":10,"area":null},{"id":"2603.07368","title":"Position: LLMs Must Use Functor-Based and RAG-Driven Bias Mitigation for Fairness","created":"2026-03-07","cited_by_count":10,"area":null},{"id":"2204.09591","title":"A Survey on Bias and Fairness in Natural Language Processing","created":"2022-03-06","cited_by_count":9,"area":null},{"id":"2305.11348","title":"In the Name of Fairness: Assessing the Bias in Clinical Record De-identification","created":"2023-05-18","cited_by_count":9,"area":null},{"id":"2310.09668","title":"Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs","created":"2023-10-14","cited_by_count":9,"area":null},{"id":"2108.12844","title":"Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification","created":"2021-08-29","cited_by_count":8,"area":null},{"id":"2302.12640","title":"In-Depth Look at Word Filling Societal Bias Measures","created":"2023-02-24","cited_by_count":8,"area":null},{"id":"2404.00897","title":"Machine Learning Robustness: A Primer","created":"2024-04-01","cited_by_count":8,"area":null},{"id":"2202.12603","title":"Language technology practitioners as language managers: arbitrating data bias and predictive bias in ASR","created":"2022-02-25","cited_by_count":7,"area":null},{"id":"2211.04281","title":"SocioProbe: What, When, and Where Language Models Learn about Sociodemographics","created":"2022-11-08","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":"2503.16541","title":"Poly-FEVER: A Multilingual Fact Verification Benchmark for Hallucination Detection in Large Language Models","created":"2025-03-19","cited_by_count":7,"area":null},{"id":"2205.06253","title":"What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics","created":"2022-05-12","cited_by_count":6,"area":null},{"id":"2209.07518","title":"Distribution Aware Metrics for Conditional Natural Language Generation","created":"2022-09-15","cited_by_count":6,"area":null},{"id":"2209.12099","title":"Controllable Text Generation for Open-Domain Creativity and Fairness","created":"2022-09-24","cited_by_count":6,"area":null},{"id":"2210.10689","title":"Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information","created":"2022-10-19","cited_by_count":6,"area":null},{"id":"2307.12973","title":"Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation","created":"2023-07-24","cited_by_count":6,"area":null},{"id":"2412.18036","title":"Explainability in Neural Networks for Natural Language Processing Tasks","created":"2024-12-23","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":"2107.10413","title":"Theoretical foundations and limits of word embeddings: what types of meaning can they capture?","created":"2021-07-22","cited_by_count":5,"area":null},{"id":"2204.09852","title":"The Risks of Machine Learning Systems","created":"2022-04-21","cited_by_count":5,"area":null},{"id":"2204.12386","title":"Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings","created":"2022-04-26","cited_by_count":5,"area":null},{"id":"2205.05128","title":"Human Language Modeling","created":"2022-05-10","cited_by_count":5,"area":null},{"id":"2208.12212","title":"Sustaining Fairness via Incremental Learning","created":"2022-08-25","cited_by_count":5,"area":null},{"id":"2211.03634","title":"No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media","created":"2022-11-07","cited_by_count":5,"area":null},{"id":"2211.04256","title":"Bridging Fairness and Environmental Sustainability in Natural Language Processing","created":"2022-11-08","cited_by_count":5,"area":null},{"id":"2305.09281","title":"On the Origins of Bias in NLP through the Lens of the Jim Code","created":"2023-05-16","cited_by_count":5,"area":null},{"id":"2305.16937","title":"Finspector: A Human-Centered Visual Inspection Tool for Exploring and Comparing Biases among Foundation Models","created":"2023-05-26","cited_by_count":5,"area":null},{"id":"2306.07500","title":"Adding guardrails to advanced chatbots","created":"2023-06-13","cited_by_count":5,"area":null},{"id":"2310.15439","title":"K-HATERS: A Hate Speech Detection Corpus in Korean with Target-Specific Ratings","created":"2023-10-24","cited_by_count":5,"area":null},{"id":"2505.15553","title":"Social Bias in Popular Question-Answering Benchmarks","created":"2025-05-21","cited_by_count":5,"area":null},{"id":"2507.07544","title":"Position: We Need An Algorithmic Understanding of Generative AI","created":"2025-07-10","cited_by_count":5,"area":null},{"id":"2208.02052","title":"Large scale analysis of gender bias and sexism in song lyrics","created":"2022-08-03","cited_by_count":4,"area":null},{"id":"2210.03353","title":"The Lifecycle of \"Facts\": A Survey of Social Bias in Knowledge Graphs","created":"2022-10-07","cited_by_count":4,"area":null},{"id":"2210.07770","title":"Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning","created":"2022-09-21","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":"2305.14757","title":"Psychological Metrics for Dialog System Evaluation","created":"2023-05-24","cited_by_count":4,"area":null},{"id":"2401.12492","title":"Comparing Pre-trained Human Language Models: Is it Better with Human Context as Groups, Individual Traits, or Both?","created":"2024-01-23","cited_by_count":4,"area":null},{"id":"2110.04001","title":"Perceived and Intended Sarcasm Detection with Graph Attention Networks","created":"2021-10-08","cited_by_count":3,"area":null},{"id":"2206.08978","title":"Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English","created":"2022-06-03","cited_by_count":3,"area":null},{"id":"2211.06409","title":"Capabilities for Better ML Engineering","created":"2022-11-11","cited_by_count":3,"area":null},{"id":"2507.00883","title":"Mathematics Isn't Culture-Free: Probing Cultural Gaps via Entity and Scenario Perturbations","created":"2025-07-01","cited_by_count":3,"area":null},{"id":"2111.00629","title":"Distantly Supervised Semantic Text Detection and Recognition for Broadcast Sports Videos Understanding","created":"2021-10-31","cited_by_count":2,"area":null},{"id":"2203.05140","title":"Speciesist Language and Nonhuman Animal Bias in English Masked Language Models","created":"2022-03-10","cited_by_count":2,"area":null}],"next_cursor":"100"}