{"total":56,"rows":[{"id":"2308.05374","title":"Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment","created":"2023-08-10","cited_by_count":401,"area":null},{"id":"2202.02950","title":"Jury Learning: Integrating Dissenting Voices into Machine Learning Models","created":"2022-02-07","cited_by_count":118,"area":null},{"id":"2106.02584","title":"Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning","created":"2021-06-04","cited_by_count":113,"area":null},{"id":"2207.00220","title":"Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset","created":"2022-07-01","cited_by_count":113,"area":null},{"id":"2102.08886","title":"Towards generalisable hate speech detection: a review on obstacles and solutions","created":"2021-02-17","cited_by_count":66,"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":"2305.16171","title":"Multi-lingual and Multi-cultural Figurative Language Understanding","created":"2023-05-25","cited_by_count":47,"area":null},{"id":"2104.06999","title":"Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media","created":"2021-04-14","cited_by_count":31,"area":null},{"id":"2311.11202","title":"Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models","created":"2023-11-19","cited_by_count":26,"area":null},{"id":"2407.08770","title":"Model Surgery: Modulating LLM's Behavior Via Simple Parameter Editing","created":"2024-07-11","cited_by_count":23,"area":"alignment"},{"id":"2106.04681","title":"Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection","created":"2021-05-25","cited_by_count":20,"area":null},{"id":"2404.01651","title":"NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps","created":"2024-04-02","cited_by_count":20,"area":null},{"id":"2107.04212","title":"Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation","created":"2021-07-09","cited_by_count":18,"area":null},{"id":"2302.09270","title":"Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements","created":"2023-02-18","cited_by_count":14,"area":null},{"id":"2404.02037","title":"MultiParaDetox: Extending Text Detoxification with Parallel Data to New Languages","created":"2024-04-02","cited_by_count":14,"area":null},{"id":"2312.01648","title":"Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation","created":"2023-12-04","cited_by_count":12,"area":null},{"id":"2106.05903","title":"Deciphering Implicit Hate: Evaluating Automated Detection Algorithms for Multimodal Hate","created":"2021-06-10","cited_by_count":8,"area":null},{"id":"2202.13056","title":"Automated Identification of Toxic Code Reviews Using ToxiCR","created":"2022-02-26","cited_by_count":8,"area":null},{"id":"2411.05854","title":"Harmful YouTube Video Detection: A Taxonomy of Online Harm and MLLMs as Alternative Annotators","created":"2024-11-06","cited_by_count":8,"area":"safety"},{"id":"2506.16393","title":"From LLM-anation to LLM-orchestrator: Coordinating Small Models for Data Labeling","created":"2025-06-19","cited_by_count":8,"area":null},{"id":"2410.03818","title":"Large Language Models can be Strong Self-Detoxifiers","created":"2024-10-04","cited_by_count":7,"area":"alignment"},{"id":"2410.15911","title":"DefVerify: Do Hate Speech Models Reflect Their Dataset's Definition?","created":"2024-10-21","cited_by_count":7,"area":null},{"id":"2205.01374","title":"Hidden behind the obvious: misleading keywords and implicitly abusive language on social media","created":"2022-05-03","cited_by_count":6,"area":null},{"id":"2106.03952","title":"Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversations","created":"2021-06-07","cited_by_count":5,"area":null},{"id":"2106.13475","title":"Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis","created":"2021-06-25","cited_by_count":5,"area":null},{"id":"2110.15871","title":"From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey","created":"2021-10-29","cited_by_count":5,"area":null},{"id":"2210.10358","title":"Leveraging a New Spanish Corpus for Multilingual and Crosslingual Metaphor Detection","created":"2022-10-19","cited_by_count":5,"area":null},{"id":"2305.12542","title":"ToxBuster: In-game Chat Toxicity Buster with BERT","created":"2023-05-21","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":"2308.09156","title":"Characterizing Information Seeking Events in Health-Related Social Discourse","created":"2023-08-17","cited_by_count":5,"area":null},{"id":"2310.18330","title":"Towards Detecting Contextual Real-Time Toxicity for In-Game Chat","created":"2023-10-20","cited_by_count":5,"area":null},{"id":"2506.06347","title":"Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection","created":"2025-06-01","cited_by_count":5,"area":null},{"id":"2306.09642","title":"Cross-Domain Toxic Spans Detection","created":"2023-06-16","cited_by_count":4,"area":null},{"id":"2311.04345","title":"A Taxonomy of Rater Disagreements: Surveying Challenges & Opportunities from the Perspective of Annotating Online Toxicity","created":"2023-11-07","cited_by_count":4,"area":null},{"id":"2410.17492","title":"BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers","created":"2024-10-23","cited_by_count":4,"area":null},{"id":"2407.01157","title":"Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models","created":"2024-07-01","cited_by_count":3,"area":null},{"id":"2509.25539","title":"Toxicity in Online Platforms and AI Systems: A Survey of Needs, Challenges, Mitigations, and Future Directions","created":"2025-09-29","cited_by_count":3,"area":null},{"id":"2109.02691","title":"SS-BERT: Mitigating Identity Terms Bias in Toxic Comment Classification by Utilising the Notion of \"Subjectivity\" and \"Identity Terms\"","created":"2021-09-06","cited_by_count":2,"area":null},{"id":"2304.09865","title":"Safer Conversational AI as a Source of User Delight","created":"2023-04-18","cited_by_count":2,"area":null},{"id":"2404.18726","title":"The Constant in HATE: Analyzing Toxicity in Reddit across Topics and Languages","created":"2024-04-29","cited_by_count":2,"area":null},{"id":"2411.06138","title":"StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms","created":"2024-11-09","cited_by_count":2,"area":"safety"},{"id":"2504.08609","title":"A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English","created":"2025-04-11","cited_by_count":2,"area":null},{"id":"2506.13513","title":"K/DA: Automated Data Generation Pipeline for Detoxifying Implicitly Offensive Language in Korean","created":"2025-06-16","cited_by_count":2,"area":null},{"id":"2104.08635","title":"UPB at SemEval-2021 Task 5: Virtual Adversarial Training for Toxic Spans Detection","created":"2021-04-17","cited_by_count":1,"area":null},{"id":"2305.15757","title":"Healing Unsafe Dialogue Responses with Weak Supervision Signals","created":"2023-05-25","cited_by_count":1,"area":null},{"id":"2308.04180","title":"Studying Socially Unacceptable Discourse Classification (SUD) through different eyes: \"Are we on the same page ?\"","created":"2023-08-08","cited_by_count":1,"area":null},{"id":"2405.13754","title":"Grounding Toxicity in Real-World Events across Languages","created":"2024-05-22","cited_by_count":1,"area":null},{"id":"2601.10294","title":"Reasoning Hijacking: The Fragility of Reasoning Alignment in Large Language Models","created":"2026-01-15","cited_by_count":1,"area":"safety"},{"id":"2101.03485","title":"Detecting Hostile Posts using Relational Graph Convolutional Network","created":"2021-01-10","cited_by_count":0,"area":null},{"id":"2104.13164","title":"UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter","created":"2021-04-27","cited_by_count":0,"area":null},{"id":"2304.06934","title":"Classification of social media Toxic comments using Machine learning models","created":"2023-04-14","cited_by_count":0,"area":null},{"id":"2311.04789","title":"Determination of toxic comments and unintended model bias minimization using Deep learning approach","created":"2023-11-08","cited_by_count":0,"area":null},{"id":"2505.02252","title":"Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language Models","created":"2025-05-04","cited_by_count":0,"area":null},{"id":"2510.15685","title":"Leveraging LLMs for Context-Aware Implicit Textual and Multimodal Hate Speech Detection","created":"2025-10-17","cited_by_count":0,"area":null},{"id":"2602.04693","title":"LinGO: A Linguistic Graph Optimization Framework with LLMs for Interpreting Intents of Online Uncivil Discourse","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2605.09955","title":"Beyond Majority Voting: Agreement-Based Clustering to Model Annotator Perspectives in Subjective NLP Tasks","created":"2026-05-11","cited_by_count":0,"area":null}],"next_cursor":null}