{"total":226,"rows":[{"id":"2309.07864","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","created":"2023-09-14","cited_by_count":1439,"area":"agents"},{"id":"2307.03109","title":"A Survey on Evaluation of Large Language Models","created":"2023-07-06","cited_by_count":1242,"area":null},{"id":"2309.00614","title":"Baseline Defenses for Adversarial Attacks Against Aligned Language Models","created":"2023-09-01","cited_by_count":651,"area":"alignment"},{"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":"2312.02003","title":"A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly","created":"2023-12-04","cited_by_count":387,"area":null},{"id":"2311.08268","title":"A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily","created":"2023-11-14","cited_by_count":259,"area":"safety"},{"id":"2310.19736","title":"Evaluating Large Language Models: A Comprehensive Survey","created":"2023-10-30","cited_by_count":202,"area":null},{"id":"2309.11751","title":"How Robust is Google's Bard to Adversarial Image Attacks?","created":"2023-09-21","cited_by_count":183,"area":"mllm"},{"id":"2406.04244","title":"Benchmark Data Contamination of Large Language Models: A Survey","created":"2024-06-06","cited_by_count":147,"area":null},{"id":"2307.11760","title":"Large Language Models Understand and Can be Enhanced by Emotional Stimuli","created":"2023-07-14","cited_by_count":146,"area":null},{"id":"2308.08833","title":"CMB: A Comprehensive Medical Benchmark in Chinese","created":"2023-08-17","cited_by_count":115,"area":null},{"id":"2310.15140","title":"AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models","created":"2023-10-23","cited_by_count":111,"area":"alignment"},{"id":"2308.14840","title":"Identifying and Mitigating the Security Risks of Generative AI","created":"2023-08-28","cited_by_count":91,"area":null},{"id":"2402.10753","title":"ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages","created":"2024-02-16","cited_by_count":82,"area":"agents"},{"id":"2311.16119","title":"Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition","created":"2023-10-24","cited_by_count":68,"area":"safety"},{"id":"2401.05778","title":"Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems","created":"2024-01-11","cited_by_count":66,"area":null},{"id":"2501.09674","title":"Authenticated Delegation and Authorized AI Agents","created":"2025-01-16","cited_by_count":65,"area":null},{"id":"2308.10819","title":"Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection","created":"2023-08-17","cited_by_count":59,"area":"safety"},{"id":"2403.15447","title":"Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression","created":"2024-03-18","cited_by_count":57,"area":null},{"id":"2402.14865","title":"Dynamic Evaluation of Large Language Models by Meta Probing Agents","created":"2024-02-21","cited_by_count":54,"area":"agents"},{"id":"2406.07057","title":"MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models","created":"2024-06-11","cited_by_count":53,"area":"mllm"},{"id":"2402.04105","title":"Measuring Implicit Bias in Explicitly Unbiased Large Language Models","created":"2024-02-06","cited_by_count":51,"area":null},{"id":"2409.12894","title":"VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation","created":"2024-09-19","cited_by_count":45,"area":"vla"},{"id":"2401.16765","title":"A Cross-Language Investigation into Jailbreak Attacks in Large Language Models","created":"2024-01-30","cited_by_count":41,"area":"safety"},{"id":"2406.10248","title":"On the Worst Prompt Performance of Large Language Models","created":"2024-06-08","cited_by_count":38,"area":null},{"id":"2308.10032","title":"GameEval: Evaluating LLMs on Conversational Games","created":"2023-08-19","cited_by_count":37,"area":null},{"id":"2505.04806","title":"Red Teaming the Mind of the Machine: A Systematic Evaluation of Prompt Injection and Jailbreak Vulnerabilities in LLMs","created":"2025-05-07","cited_by_count":34,"area":"safety"},{"id":"2311.09447","title":"How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities","created":"2023-11-15","cited_by_count":33,"area":null},{"id":"2309.01686","title":"MathAttack: Attacking Large Language Models Towards Math Solving Ability","created":"2023-09-04","cited_by_count":32,"area":null},{"id":"2309.12444","title":"Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI","created":"2023-09-21","cited_by_count":32,"area":null},{"id":"2403.00025","title":"On the Challenges and Opportunities in Generative AI","created":"2024-02-28","cited_by_count":31,"area":null},{"id":"2404.16966","title":"Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks","created":"2024-04-25","cited_by_count":31,"area":null},{"id":"2411.05345","title":"Reasoning Robustness of LLMs to Adversarial Typographical Errors","created":"2024-11-08","cited_by_count":31,"area":"lr"},{"id":"2402.15833","title":"Prompt Perturbation Consistency Learning for Robust Language Models","created":"2024-02-24","cited_by_count":26,"area":null},{"id":"2504.14772","title":"Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions","created":"2025-04-20","cited_by_count":26,"area":"distill"},{"id":"2310.01651","title":"Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations","created":"2023-10-02","cited_by_count":25,"area":"mllm"},{"id":"2503.11751","title":"reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs","created":"2025-03-14","cited_by_count":25,"area":"alignment"},{"id":"2309.04369","title":"Beyond Static Datasets: A Deep Interaction Approach to LLM Evaluation","created":"2023-09-08","cited_by_count":24,"area":null},{"id":"2401.11943","title":"Benchmarking Large Multimodal Models against Common Corruptions","created":"2024-01-22","cited_by_count":24,"area":"lr"},{"id":"2404.07584","title":"UltraEval: A Lightweight Platform for Flexible and Comprehensive Evaluation for LLMs","created":"2024-04-11","cited_by_count":24,"area":null},{"id":"2406.14859","title":"From LLMs to MLLMs: Exploring the Landscape of Multimodal Jailbreaking","created":"2024-06-21","cited_by_count":24,"area":"mllm"},{"id":"2505.20322","title":"Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms","created":"2025-05-23","cited_by_count":24,"area":null},{"id":"2309.17415","title":"Intuitive or Dependent? Investigating LLMs' Behavior Style to Conflicting Prompts","created":"2023-09-29","cited_by_count":23,"area":"rag"},{"id":"2406.05392","title":"Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey","created":"2024-06-08","cited_by_count":23,"area":null},{"id":"2408.06318","title":"Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example","created":"2024-08-12","cited_by_count":22,"area":"agents"},{"id":"2410.11005","title":"Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks","created":"2024-10-14","cited_by_count":22,"area":"lr"},{"id":"2509.10147","title":"Virtual Agent Economies","created":"2025-09-12","cited_by_count":21,"area":null},{"id":"2603.13285","title":"Brittlebench: Quantifying LLM robustness via prompt sensitivity","created":"2026-02-27","cited_by_count":21,"area":null},{"id":"2308.04945","title":"LLMeBench: A Flexible Framework for Accelerating LLMs Benchmarking","created":"2023-08-09","cited_by_count":20,"area":null},{"id":"2312.06056","title":"METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities","created":"2023-12-11","cited_by_count":20,"area":null},{"id":"2404.09754","title":"Resilience of Large Language Models for Noisy Instructions","created":"2024-04-15","cited_by_count":20,"area":null},{"id":"2406.03009","title":"Unveiling Selection Biases: Exploring Order and Token Sensitivity in Large Language Models","created":"2024-06-05","cited_by_count":20,"area":null},{"id":"2406.19783","title":"NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations","created":"2024-06-28","cited_by_count":20,"area":null},{"id":"2509.21834","title":"RobustFlow: Towards Robust Agentic Workflow Generation","created":"2025-09-26","cited_by_count":20,"area":"agents"},{"id":"2311.18805","title":"Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text","created":"2023-11-30","cited_by_count":19,"area":null},{"id":"2405.20902","title":"Preemptive Answer \"Attacks\" on Chain-of-Thought Reasoning","created":"2024-05-31","cited_by_count":19,"area":"lr"},{"id":"2410.12656","title":"Evaluating Morphological Compositional Generalization in Large Language Models","created":"2024-10-16","cited_by_count":19,"area":null},{"id":"2502.11767","title":"From Selection to Generation: A Survey of LLM-based Active Learning","created":"2025-02-17","cited_by_count":19,"area":null},{"id":"2503.00137","title":"SCORE: Systematic COnsistency and Robustness Evaluation for Large Language Models","created":"2025-02-28","cited_by_count":19,"area":null},{"id":"2405.00622","title":"Causal Evaluation of Language Models","created":"2024-05-01","cited_by_count":18,"area":"lr"},{"id":"2402.11138","title":"Contrastive Instruction Tuning","created":"2024-02-17","cited_by_count":17,"area":null},{"id":"2404.17642","title":"Empowering Large Language Models for Textual Data Augmentation","created":"2024-04-26","cited_by_count":17,"area":null},{"id":"2407.05271","title":"Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions","created":"2024-07-07","cited_by_count":17,"area":null},{"id":"2311.14966","title":"Walking a Tightrope -- Evaluating Large Language Models in High-Risk Domains","created":"2023-11-25","cited_by_count":15,"area":null},{"id":"2311.10117","title":"Automatic Engineering of Long Prompts","created":"2023-11-16","cited_by_count":14,"area":null},{"id":"2308.04813","title":"CLEVA: Chinese Language Models EVAluation Platform","created":"2023-08-09","cited_by_count":13,"area":null},{"id":"2406.11020","title":"RUPBench: Benchmarking Reasoning Under Perturbations for Robustness Evaluation in Large Language Models","created":"2024-06-16","cited_by_count":13,"area":"lr"},{"id":"2408.13533","title":"Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models","created":"2024-08-24","cited_by_count":13,"area":"rag"},{"id":"2601.04583","title":"Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundaries","created":"2026-01-08","cited_by_count":13,"area":"agents"},{"id":"2503.23804","title":"DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents","created":"2025-03-31","cited_by_count":12,"area":"agents"},{"id":"2506.19806","title":"LLM-Based Social Simulations Require a Boundary","created":"2025-06-24","cited_by_count":12,"area":null},{"id":"2511.02108","title":"Metamorphic Testing of Large Language Models for Natural Language Processing","created":"2025-11-03","cited_by_count":12,"area":null},{"id":"2407.08983","title":"Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations","created":"2024-07-12","cited_by_count":11,"area":null},{"id":"2410.01824","title":"AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers","created":"2024-09-16","cited_by_count":11,"area":null},{"id":"2507.22171","title":"Enhancing Jailbreak Attacks on LLMs via Persona Prompts","created":"2025-07-28","cited_by_count":11,"area":"safety"},{"id":"2604.23338","title":"A Systematic Survey of Security Threats and Defenses in LLM-Based AI Agents: A Layered Attack Surface Framework","created":"2026-04-25","cited_by_count":11,"area":"agents"},{"id":"2410.13198","title":"Failing Forward: Improving Generative Error Correction for ASR with Synthetic Data and Retrieval Augmentation","created":"2024-10-17","cited_by_count":10,"area":"rag"},{"id":"2410.20940","title":"Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models","created":"2024-10-28","cited_by_count":10,"area":null},{"id":"2508.11383","title":"When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs","created":"2025-08-15","cited_by_count":10,"area":null},{"id":"2509.01301","title":"Culture is Everywhere: A Call for Intentionally Cultural Evaluation","created":"2025-09-01","cited_by_count":10,"area":"alignment"},{"id":"2510.13855","title":"Harnessing Consistency for Robust Test-Time LLM Ensemble","created":"2025-10-12","cited_by_count":10,"area":null},{"id":"2609.31142","title":"JevAdvBench: A Benchmark and Black-Box Attacks for Reinforcement Learning for Calibrated Decisions Models","created":"2026-09-25","cited_by_count":10,"area":"lr"},{"id":"2403.03788","title":"PPTC-R benchmark: Towards Evaluating the Robustness of Large Language Models for PowerPoint Task Completion","created":"2024-03-06","cited_by_count":9,"area":null},{"id":"2404.13060","title":"The Necessity of AI Audit Standards Boards","created":"2024-04-11","cited_by_count":9,"area":null},{"id":"2505.14412","title":"PRL: Prompts from Reinforcement Learning","created":"2025-05-20","cited_by_count":9,"area":"lr"},{"id":"2507.00490","title":"Just Noticeable Difference for Large Multimodal Models","created":"2025-07-01","cited_by_count":9,"area":"mllm"},{"id":"2510.09536","title":"Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors","created":"2025-10-10","cited_by_count":9,"area":null},{"id":"2404.05783","title":"A Survey on Responsible Generative AI: What to Generate and What Not","created":"2024-04-08","cited_by_count":8,"area":null},{"id":"2407.02596","title":"Towards More Realistic Extraction Attacks: An Adversarial Perspective","created":"2024-07-02","cited_by_count":8,"area":null},{"id":"2407.04046","title":"Systematic Task Exploration with LLMs: A Study in Citation Text Generation","created":"2024-07-04","cited_by_count":8,"area":null},{"id":"2504.07801","title":"FairEval: Evaluating Fairness in LLM-Based Recommendations with Personality Awareness","created":"2025-04-10","cited_by_count":8,"area":null},{"id":"2505.23715","title":"Don't Take the Premise for Granted: Evaluating the Premise Critique Ability of Large Language Models","created":"2025-05-29","cited_by_count":8,"area":"lr"},{"id":"2308.07847","title":"Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Models","created":"2023-08-15","cited_by_count":7,"area":"safety"},{"id":"2405.20315","title":"ANAH: Analytical Annotation of Hallucinations in Large Language Models","created":"2024-05-30","cited_by_count":7,"area":null},{"id":"2406.06590","title":"Are LLMs classical or nonmonotonic reasoners? Lessons from generics","created":"2024-06-05","cited_by_count":7,"area":"lr"},{"id":"2406.11353","title":"$\\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts","created":"2024-06-17","cited_by_count":7,"area":"moe"},{"id":"2409.11149","title":"SAGED: A Holistic Bias-Benchmarking Pipeline for Language Models with Customisable Fairness Calibration","created":"2024-09-17","cited_by_count":6,"area":null},{"id":"2412.02159","title":"Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach","created":"2024-12-03","cited_by_count":6,"area":"safety"},{"id":"2501.13115","title":"Dagger Behind Smile: Fool LLMs with a Happy Ending Story","created":"2025-01-19","cited_by_count":6,"area":"safety"},{"id":"2502.12896","title":"None of the Others: a General Technique to Distinguish Reasoning from Memorization in Multiple-Choice LLM Evaluation Benchmarks","created":"2025-02-18","cited_by_count":6,"area":"lr"}],"next_cursor":"100"}