{"total":137,"rows":[{"id":"2402.05044","title":"SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models","created":"2024-02-07","cited_by_count":228,"area":null},{"id":"2411.11581","title":"OASIS: Open Agent Social Interaction Simulations with One Million Agents","created":"2024-11-18","cited_by_count":132,"area":null},{"id":"2402.09283","title":"Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey","created":"2024-02-14","cited_by_count":130,"area":null},{"id":"2407.18418","title":"Know Your Limits: A Survey of Abstention in Large Language Models","created":"2024-07-25","cited_by_count":121,"area":null},{"id":"2407.12043","title":"The Art of Saying No: Contextual Noncompliance in Language Models","created":"2024-07-02","cited_by_count":105,"area":null},{"id":"2407.06551","title":"OffsetBias: Leveraging Debiased Data for Tuning Evaluators","created":"2024-07-09","cited_by_count":94,"area":null},{"id":"2409.01586","title":"Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation","created":"2024-09-03","cited_by_count":92,"area":null},{"id":"2311.08370","title":"SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models","created":"2023-11-14","cited_by_count":76,"area":null},{"id":"2407.00128","title":"When Search Engine Services meet Large Language Models: Visions and Challenges","created":"2024-06-28","cited_by_count":59,"area":null},{"id":"2406.06144","title":"Language Models Resist Alignment: Evidence From Data Compression","created":"2024-06-10","cited_by_count":53,"area":null},{"id":"2508.09224","title":"From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training","created":"2025-08-12","cited_by_count":52,"area":null},{"id":"2311.10766","title":"Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values","created":"2023-11-15","cited_by_count":50,"area":null},{"id":"2402.04247","title":"Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy","created":"2024-02-06","cited_by_count":49,"area":null},{"id":"2410.03415","title":"Surgical, Cheap, and Flexible: Mitigating False Refusal in Language Models via Single Vector Ablation","created":"2024-10-04","cited_by_count":48,"area":null},{"id":"2510.07284","title":"Online Rubrics Elicitation from Pairwise Comparisons","created":"2025-10-08","cited_by_count":46,"area":null},{"id":"2505.17306","title":"Refusal Direction is Universal Across Safety-Aligned Languages","created":"2025-05-22","cited_by_count":38,"area":null},{"id":"2510.12633","title":"Laminar: A Scalable Asynchronous RL Post-Training Framework","created":"2025-10-14","cited_by_count":37,"area":null},{"id":"2310.15469","title":"The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks","created":"2023-10-24","cited_by_count":36,"area":null},{"id":"2412.13879","title":"Crabs: Consuming Resource via Auto-generation for LLM-DoS Attack under Black-box Settings","created":"2024-12-18","cited_by_count":35,"area":null},{"id":"2312.04828","title":"HuRef: HUman-REadable Fingerprint for Large Language Models","created":"2023-12-08","cited_by_count":34,"area":null},{"id":"2402.11889","title":"ROSE Doesn't Do That: Boosting the Safety of Instruction-Tuned Large Language Models with Reverse Prompt Contrastive Decoding","created":"2024-02-19","cited_by_count":32,"area":null},{"id":"2505.18889","title":"Security Concerns for Large Language Models: A Survey","created":"2025-05-24","cited_by_count":29,"area":null},{"id":"2505.24535","title":"Beyond Linear Steering: Unified Multi-Attribute Control for Language Models","created":"2025-05-30","cited_by_count":25,"area":null},{"id":"2503.06550","title":"BingoGuard: LLM Content Moderation Tools with Risk Levels","created":"2025-03-09","cited_by_count":21,"area":null},{"id":"2505.12038","title":"Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets","created":"2025-05-17","cited_by_count":18,"area":null},{"id":"2403.13213","title":"From Representational Harms to Quality-of-Service Harms: A Case Study on Llama 2 Safety Safeguards","created":"2024-03-20","cited_by_count":17,"area":null},{"id":"2505.16975","title":"SWE-Dev: Evaluating and Training Autonomous Feature-Driven Software Development","created":"2025-05-22","cited_by_count":16,"area":null},{"id":"2311.16989","title":"ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?","created":"2023-11-28","cited_by_count":15,"area":null},{"id":"2501.12689","title":"IC-Cache: Efficient Large Language Model Serving via In-context Caching","created":"2025-01-22","cited_by_count":13,"area":null},{"id":"2505.17646","title":"Unveiling the Basin-Like Loss Landscape in Large Language Models","created":"2025-05-23","cited_by_count":13,"area":null},{"id":"2509.25369","title":"Generative Value Conflicts Reveal LLM Priorities","created":"2025-09-29","cited_by_count":13,"area":null},{"id":"2410.19160","title":"Adversarial Attacks on Large Language Models Using Regularized Relaxation","created":"2024-10-24","cited_by_count":12,"area":null},{"id":"2502.16776","title":"AISafetyLab: A Comprehensive Framework for AI Safety Evaluation and Improvement","created":"2025-02-24","cited_by_count":12,"area":null},{"id":"2506.00911","title":"Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models","created":"2025-06-01","cited_by_count":12,"area":null},{"id":"2512.06547","title":"A-3PO: Accelerating Asynchronous LLM Training with Staleness-aware Proximal Policy Approximation","created":"2025-12-06","cited_by_count":12,"area":null},{"id":"2504.01212","title":"Cooper: A Library for Constrained Optimization in Deep Learning","created":"2025-04-01","cited_by_count":11,"area":null},{"id":"2511.04962","title":"Too Good to be Bad: On the Failure of LLMs to Role-Play Villains","created":"2025-11-07","cited_by_count":11,"area":null},{"id":"2505.21344","title":"The Multilingual Divide and Its Impact on Global AI Safety","created":"2025-05-27","cited_by_count":10,"area":null},{"id":"2503.08796","title":"Robust Multi-Objective Controlled Decoding of Large Language Models","created":"2025-03-11","cited_by_count":9,"area":null},{"id":"2505.16245","title":"Diverse, not Short: A Length-Controlled Data Selection Strategy for Improving Response Diversity of Language Models","created":"2025-05-22","cited_by_count":9,"area":null},{"id":"2512.11437","title":"CLINIC: Evaluating Multilingual Trustworthiness in Language Models for Healthcare","created":"2025-12-12","cited_by_count":9,"area":null},{"id":"2407.02518","title":"INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness","created":"2024-06-23","cited_by_count":8,"area":null},{"id":"2411.08243","title":"Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset","created":"2024-11-12","cited_by_count":8,"area":null},{"id":"2412.13341","title":"Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing","created":"2024-12-17","cited_by_count":8,"area":null},{"id":"2503.19257","title":"SCI-IDEA: Context-Aware Scientific Ideation Using Token and Sentence Embeddings","created":"2025-03-25","cited_by_count":8,"area":null},{"id":"2505.18513","title":"Enhancing Training Data Attribution with Representational Optimization","created":"2025-05-24","cited_by_count":8,"area":null},{"id":"2405.09794","title":"Human-AI Safety: A Descendant of Generative AI and Control Systems Safety","created":"2024-05-16","cited_by_count":7,"area":null},{"id":"2406.06559","title":"Harnessing Business and Media Insights with Large Language Models","created":"2024-06-02","cited_by_count":7,"area":null},{"id":"2501.06911","title":"Risk-Averse Finetuning of Large Language Models","created":"2025-01-12","cited_by_count":7,"area":null},{"id":"2502.00840","title":"Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense","created":"2025-02-02","cited_by_count":7,"area":null},{"id":"2502.19320","title":"Shh, don't say that! Domain Certification in LLMs","created":"2025-02-26","cited_by_count":7,"area":null},{"id":"2411.06824","title":"Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs","created":"2024-11-11","cited_by_count":6,"area":null},{"id":"2502.11269","title":"Unlocking the Potential of Generative AI through Neuro-Symbolic Architectures: Benefits and Limitations","created":"2025-02-16","cited_by_count":6,"area":null},{"id":"2512.05671","title":"ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education","created":"2025-12-05","cited_by_count":6,"area":null},{"id":"2503.21383","title":"Controlling Large Language Model with Latent Actions","created":"2025-03-27","cited_by_count":5,"area":null},{"id":"2504.05321","title":"VALUE: Value-Aware Large Language Model for Query Rewriting via Weighted Trie in Sponsored Search","created":"2025-02-25","cited_by_count":5,"area":null},{"id":"2505.20628","title":"Position: Adopt Constraints Over Fixed Penalties in Deep Learning","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2509.07287","title":"Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm","created":"2025-09-08","cited_by_count":5,"area":null},{"id":"2409.09601","title":"A Survey of Foundation Models for Music Understanding","created":"2024-09-15","cited_by_count":4,"area":null},{"id":"2502.02444","title":"Generative Psycho-Lexical Approach for Constructing Value Systems in Large Language Models","created":"2025-02-04","cited_by_count":4,"area":null},{"id":"2511.00382","title":"Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs","created":"2025-11-01","cited_by_count":4,"area":null},{"id":"2602.11000","title":"Fine-Tuning GPT-5 for GPU Kernel Generation","created":"2026-02-11","cited_by_count":4,"area":null},{"id":"2604.09107","title":"TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training","created":"2026-04-10","cited_by_count":4,"area":null},{"id":"2605.07386","title":"Convex Optimization with Nested Evolving Feasible Sets","created":"2026-05-08","cited_by_count":4,"area":null},{"id":"2503.22764","title":"Boosting Large Language Models with Mask Fine-Tuning","created":"2025-03-27","cited_by_count":3,"area":null},{"id":"2507.21276","title":"LeMix: Unified Scheduling for LLM Training and Inference on Multi-GPU Systems","created":"2025-07-28","cited_by_count":3,"area":null},{"id":"2508.18739","title":"Beyond Quality: Unlocking Diversity in Ad Headline Generation with Large Language Models","created":"2025-08-26","cited_by_count":3,"area":null},{"id":"2510.12072","title":"EmboMatrix: A Scalable Training-Ground for Embodied Decision-Making","created":"2025-10-14","cited_by_count":3,"area":null},{"id":"2512.20061","title":"Scaling Reinforcement Learning for Content Moderation with Large Language Models","created":"2025-12-23","cited_by_count":3,"area":null},{"id":"2601.22452","title":"Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction","created":"2026-01-30","cited_by_count":3,"area":null},{"id":"2410.01098","title":"Exploring Gen-AI applications in building research and industry: A review","created":"2024-10-01","cited_by_count":2,"area":null},{"id":"2410.12130","title":"Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning","created":"2024-10-16","cited_by_count":2,"area":null},{"id":"2410.18841","title":"From Efficiency to Equity: Measuring Fairness in Preference Learning","created":"2024-10-24","cited_by_count":2,"area":null},{"id":"2502.12565","title":"Self Iterative Label Refinement via Robust Unlabeled Learning","created":"2025-02-18","cited_by_count":2,"area":null},{"id":"2508.19546","title":"Language Models Identify Ambiguities and Exploit Loopholes","created":"2025-08-27","cited_by_count":2,"area":null},{"id":"2510.00232","title":"BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses","created":"2025-09-30","cited_by_count":2,"area":null},{"id":"2511.02495","title":"DetectiumFire: A Comprehensive Multi-modal Dataset Bridging Vision and Language for Fire Understanding","created":"2025-11-04","cited_by_count":2,"area":null},{"id":"2602.07963","title":"Lost in Translation? A Comparative Study on the Cross-Lingual Transfer of Composite Harms","created":"2026-02-08","cited_by_count":2,"area":null},{"id":"2605.06901","title":"Reflections and New Directions for Human-Centered Large Language Models","created":"2026-05-07","cited_by_count":2,"area":null},{"id":"2605.09640","title":"Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning","created":"2026-05-10","cited_by_count":2,"area":null},{"id":"2605.29267","title":"When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop","created":"2026-05-28","cited_by_count":2,"area":null},{"id":"2403.15045","title":"DP-Dueling: Learning from Preference Feedback without Compromising User Privacy","created":"2024-03-22","cited_by_count":1,"area":null},{"id":"2407.13048","title":"Establishing Knowledge Preference in Language Models","created":"2024-07-17","cited_by_count":1,"area":null},{"id":"2501.13727","title":"Scalable Safe Multi-Agent Reinforcement Learning for Multi-Agent System","created":"2025-01-23","cited_by_count":1,"area":null},{"id":"2505.18680","title":"$PD^3F$: A Pluggable and Dynamic DoS-Defense Framework Against Resource Consumption Attacks Targeting Large Language Models","created":"2025-05-24","cited_by_count":1,"area":null},{"id":"2505.21478","title":"Policy Optimized Text-to-Image Pipeline Design","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2506.09496","title":"EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2509.03526","title":"Enhancing Speech Large Language Models through Reinforced Behavior Alignment","created":"2025-08-25","cited_by_count":1,"area":null},{"id":"2509.16400","title":"'Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ?","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2509.22500","title":"Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2511.00220","title":"Iterative Foundation Model Fine-Tuning on Multiple Rewards","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2601.03788","title":"Criminal Liability of Generative Artificial Intelligence Providers for User-Generated Child Sexual Abuse Material","created":"2026-01-07","cited_by_count":1,"area":null},{"id":"2601.21439","title":"The Paradox of Robustness: Decoupling Rule-Based Logic from Affective Noise in High-Stakes Decision-Making","created":"2026-01-29","cited_by_count":1,"area":null},{"id":"2601.23094","title":"Safer Policy Compliance with Dynamic Epistemic Fallback","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2601.23157","title":"No More, No Less: Least-Privilege Language Models","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2603.10072","title":"Why LLMs Fail: A Failure Analysis and Partial Success Measurement for Automated Security Patch Generation","created":"2026-03-10","cited_by_count":1,"area":null},{"id":"2604.07655","title":"Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs","created":"2026-04-08","cited_by_count":1,"area":null},{"id":"2604.11120","title":"Persona Non Grata: Single-Method Safety Evaluation Is Incomplete for Persona-Imbued LLMs","created":"2026-04-13","cited_by_count":1,"area":null},{"id":"2604.26577","title":"Benchmarking the Safety of Large Language Models for Robotic Health Attendant Control","created":"2026-04-29","cited_by_count":1,"area":null},{"id":"2604.28020","title":"Cost-Aware Learning","created":"2026-04-30","cited_by_count":1,"area":null}],"next_cursor":"100"}