Responsible AI

Reveal and Release: Iterative LLM Unlearning with Self-generated Data EMNLP 2025 Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs) ICLR 2025 ReviewRL: Towards Automated Scientific Review with RL EMNLP 2025 Reward Model Perspectives: Whose Opinions Do Reward Models Reward? EMNLP 2025 ‘Rich Dad, Poor Lad’: How do Large Language Models Contextualize Socioeconomic Factors in College Admission ? EMNLP 2025 Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness ACL 2025 Root Defense Strategies: Ensuring Safety of LLM at the Decoding Level ACL 2025 R.R.: Unveiling LLM Training Privacy through Recollection and Ranking ACL 2025 R-TOFU: Unlearning in Large Reasoning Models EMNLP 2025 RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios? AAAI 2025 Rubrik’s Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset ACL 2025 SafeArena: Evaluating the Safety of Autonomous Web Agents ICML 2025 Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets ICML 2025 SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning ACL 2025 Safe Inputs but Unsafe Output: Benchmarking Cross-modality Safety Alignment of Large Vision-Language Models NAACL 2025 SafeKey: Amplifying Aha-Moment Insights for Safety Reasoning EMNLP 2025 SafeLawBench: Towards Safe Alignment of Large Language Models ACL 2025 SAFENUDGE: Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs EMNLP 2025 SafePersuasion: A Dataset, Taxonomy, and Baselines for Analysis of Rational Persuasion and Manipulation IJCNLP 2025 SafeQuant: LLM Safety Analysis via Quantized Gradient Inspection NAACL 2025 SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model ACL 2025 SafeSwitch: Steering Unsafe LLM Behavior via Internal Activation Signals EMNLP 2025 SafeToolBench: Pioneering a Prospective Benchmark to Evaluating Tool Utilization Safety in LLMs EMNLP 2025 Safety Alignment Can Be Not Superficial With Explicit Safety Signals ICML 2025 Safety Alignment Should be Made More Than Just a Few Tokens Deep ICLR 2025