{"total":332,"rows":[{"id":"2406.20094","title":"Scaling Synthetic Data Creation with 1,000,000,000 Personas","created":"2024-06-28","cited_by_count":417,"area":"synth"},{"id":"2506.09038","title":"AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions","created":"2025-06-10","cited_by_count":145,"area":"lr"},{"id":"2504.01990","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","created":"2025-03-31","cited_by_count":126,"area":"agents"},{"id":"2410.08948","title":"Emergent social conventions and collective bias in LLM populations","created":"2024-10-11","cited_by_count":123,"area":null},{"id":"2412.05563","title":"A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions","created":"2024-12-07","cited_by_count":121,"area":null},{"id":"2406.13629","title":"InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales","created":"2024-06-19","cited_by_count":101,"area":"rag"},{"id":"2409.17504","title":"HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection","created":"2024-09-26","cited_by_count":99,"area":null},{"id":"2402.15570","title":"Fast Adversarial Attacks on Language Models In One GPU Minute","created":"2024-02-23","cited_by_count":88,"area":"safety"},{"id":"2410.11779","title":"MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation","created":"2024-10-15","cited_by_count":88,"area":"mllm"},{"id":"2407.08223","title":"Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting","created":"2024-07-11","cited_by_count":77,"area":"rag"},{"id":"2503.18102","title":"AgentRxiv: Towards Collaborative Autonomous Research","created":"2025-03-23","cited_by_count":72,"area":null},{"id":"2410.18927","title":"SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models","created":"2024-10-24","cited_by_count":69,"area":"safety"},{"id":"2402.01822","title":"Building Guardrails for Large Language Models","created":"2024-02-02","cited_by_count":65,"area":"safety"},{"id":"2501.10326","title":"Large language models for automated scholarly paper review: A survey","created":"2025-01-17","cited_by_count":61,"area":null},{"id":"2504.06514","title":"Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?","created":"2025-04-09","cited_by_count":58,"area":"lr"},{"id":"2506.19676","title":"A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures","created":"2025-06-24","cited_by_count":57,"area":"agents"},{"id":"2402.17385","title":"Determinants of LLM-assisted Decision-Making","created":"2024-02-27","cited_by_count":56,"area":null},{"id":"2410.08109","title":"A Closer Look at Machine Unlearning for Large Language Models","created":"2024-10-10","cited_by_count":56,"area":"safety"},{"id":"2408.08862","title":"Visual Agents as Fast and Slow Thinkers","created":"2024-08-16","cited_by_count":53,"area":"lr"},{"id":"2409.14674","title":"RACER: Rich Language-Guided Failure Recovery Policies for Imitation Learning","created":"2024-09-23","cited_by_count":49,"area":"offlinerl"},{"id":"2510.06265","title":"Large Language Models Hallucination: A Comprehensive Survey","created":"2025-10-05","cited_by_count":49,"area":null},{"id":"2403.08946","title":"Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era","created":"2024-03-13","cited_by_count":46,"area":null},{"id":"2404.06757","title":"Language Generation in the Limit","created":"2024-04-10","cited_by_count":40,"area":null},{"id":"2407.09007","title":"Benchmarking Language Model Creativity: A Case Study on Code Generation","created":"2024-07-12","cited_by_count":40,"area":null},{"id":"2405.13873","title":"FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering","created":"2024-05-22","cited_by_count":39,"area":"lr"},{"id":"2406.06302","title":"Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks","created":"2024-06-10","cited_by_count":38,"area":"safety"},{"id":"2501.02765","title":"Visual Large Language Models for Generalized and Specialized Applications","created":"2025-01-06","cited_by_count":36,"area":"mllm"},{"id":"2410.13509","title":"RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards","created":"2024-10-17","cited_by_count":33,"area":"rag"},{"id":"2502.02871","title":"Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning","created":"2025-02-05","cited_by_count":33,"area":"lr"},{"id":"2401.17244","title":"LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation","created":"2024-01-30","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":"2410.16130","title":"Can Large Audio-Language Models Truly Hear? Tackling Hallucinations with Multi-Task Assessment and Stepwise Audio Reasoning","created":"2024-10-21","cited_by_count":31,"area":"lr"},{"id":"2501.01306","title":"Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking","created":"2025-01-02","cited_by_count":31,"area":"lr"},{"id":"2506.19923","title":"Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs","created":"2025-06-24","cited_by_count":31,"area":"agents"},{"id":"2409.03219","title":"Content Moderation by LLM: From Accuracy to Legitimacy","created":"2024-09-05","cited_by_count":30,"area":null},{"id":"2505.20862","title":"AVCD: Mitigating Hallucinations in Audio-Visual Large Language Models through Contrastive Decoding","created":"2025-05-27","cited_by_count":30,"area":"mllm"},{"id":"2410.07295","title":"IterGen: Iterative Semantic-aware Structured LLM Generation with Backtracking","created":"2024-10-09","cited_by_count":29,"area":null},{"id":"2411.14258","title":"Knowledge Graphs, Large Language Models, and Hallucinations: An NLP Perspective","created":"2024-11-21","cited_by_count":29,"area":null},{"id":"2411.15364","title":"Exploring Facets of Language Generation in the Limit","created":"2024-11-22","cited_by_count":28,"area":null},{"id":"2509.25760","title":"TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning","created":"2025-09-30","cited_by_count":27,"area":null},{"id":"2410.03334","title":"An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation","created":"2024-10-04","cited_by_count":25,"area":"mechinterp"},{"id":"2404.03118","title":"LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models","created":"2024-04-03","cited_by_count":24,"area":"mllm"},{"id":"2501.18081","title":"Normative Evaluation of Large Language Models with Everyday Moral Dilemmas","created":"2025-01-30","cited_by_count":24,"area":null},{"id":"2502.15844","title":"Hallucination Detection in Large Language Models with Metamorphic Relations","created":"2025-02-20","cited_by_count":24,"area":null},{"id":"2505.17716","title":"Get Experience from Practice: LLM Agents with Record & Replay","created":"2025-05-23","cited_by_count":23,"area":"agents"},{"id":"2404.17833","title":"Testing and Understanding Erroneous Planning in LLM Agents through Synthesized User Inputs","created":"2024-04-27","cited_by_count":22,"area":"agents"},{"id":"2504.14370","title":"Density Measures for Language Generation","created":"2025-04-19","cited_by_count":21,"area":null},{"id":"2507.04136","title":"A Technical Survey of Reinforcement Learning Techniques for Large Language Models","created":"2025-07-05","cited_by_count":21,"area":"lr"},{"id":"2406.11277","title":"Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector","created":"2024-06-17","cited_by_count":20,"area":"agents"},{"id":"2412.06512","title":"The Fusion of Large Language Models and Formal Methods for Trustworthy AI Agents: A Roadmap","created":"2024-12-09","cited_by_count":20,"area":"agents"},{"id":"2411.16771","title":"VidHal: Benchmarking Temporal Hallucinations in Vision LLMs","created":"2024-11-25","cited_by_count":19,"area":null},{"id":"2502.07143","title":"Ask Patients with Patience: Enabling LLMs for Human-Centric Medical Dialogue with Grounded Reasoning","created":"2025-02-11","cited_by_count":19,"area":"lr"},{"id":"2504.17309","title":"CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Quality","created":"2025-04-24","cited_by_count":19,"area":null},{"id":"2408.11338","title":"Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond","created":"2024-08-21","cited_by_count":18,"area":null},{"id":"2409.06450","title":"Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles","created":"2024-09-10","cited_by_count":18,"area":"mllm"},{"id":"2409.13174","title":"Manipulation Facing Threats: Evaluating Physical Vulnerabilities in End-to-End Vision Language Action Models","created":"2024-09-20","cited_by_count":18,"area":"mllm"},{"id":"2501.11551","title":"PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation","created":"2025-01-20","cited_by_count":18,"area":"rag"},{"id":"2402.09801","title":"EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models","created":"2024-02-15","cited_by_count":17,"area":"mllm"},{"id":"2408.15533","title":"LRP4RAG: Detecting Hallucinations in Retrieval-Augmented Generation via Layer-wise Relevance Propagation","created":"2024-08-28","cited_by_count":17,"area":"rag"},{"id":"2505.18585","title":"RvLLM: LLM Runtime Verification with Domain Knowledge","created":"2025-05-24","cited_by_count":17,"area":null},{"id":"2510.22422","title":"Group size effects and collective misalignment in LLM multi-agent systems","created":"2025-10-25","cited_by_count":16,"area":"agents"},{"id":"2412.06474","title":"Enhancing Vision-Language Model Reliability with Uncertainty-Guided Dropout Decoding","created":"2024-12-09","cited_by_count":15,"area":"mllm"},{"id":"2504.17004","title":"(Im)possibility of Automated Hallucination Detection in Large Language Models","created":"2025-04-23","cited_by_count":15,"area":null},{"id":"2411.10242","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","created":"2024-11-15","cited_by_count":14,"area":null},{"id":"2510.04849","title":"When Models Lie, We Learn: Multilingual Span-Level Hallucination Detection with PsiloQA","created":"2025-10-06","cited_by_count":14,"area":null},{"id":"2402.12590","title":"Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation","created":"2024-02-19","cited_by_count":13,"area":null},{"id":"2406.17642","title":"Banishing LLM Hallucinations Requires Rethinking Generalization","created":"2024-06-25","cited_by_count":13,"area":"lr"},{"id":"2408.01112","title":"Agentic LLM Workflows for Generating Patient-Friendly Medical Reports","created":"2024-08-02","cited_by_count":13,"area":"agents"},{"id":"2502.11948","title":"HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detection","created":"2025-02-17","cited_by_count":13,"area":null},{"id":"2501.13946","title":"Hallucination Mitigation using Agentic AI Natural Language-Based Frameworks","created":"2025-01-19","cited_by_count":12,"area":"agents"},{"id":"2402.11176","title":"KnowTuning: Knowledge-aware Fine-tuning for Large Language Models","created":"2024-02-17","cited_by_count":11,"area":null},{"id":"2410.02899","title":"FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMs","created":"2024-10-03","cited_by_count":11,"area":null},{"id":"2410.05051","title":"ComDrive: Comfort-Oriented End-to-End Autonomous Driving","created":"2024-10-07","cited_by_count":11,"area":"diffusion"},{"id":"2503.11302","title":"Are formal and functional linguistic mechanisms dissociated in language models?","created":"2025-03-14","cited_by_count":11,"area":null},{"id":"2509.22256","title":"Secure and Efficient Access Control for Computer-Use Agents via Context Space","created":"2025-09-26","cited_by_count":11,"area":"agents"},{"id":"2512.19466","title":"Epistemological Fault Lines Between Human and Artificial Intelligence","created":"2025-12-22","cited_by_count":11,"area":null},{"id":"2405.02228","title":"Abstention vs. Hallucination: Benchmarking LLM Source Attribution for Scientific Citations","created":"2024-05-03","cited_by_count":10,"area":"rag"},{"id":"2505.09056","title":"A Comprehensive Analysis of Large Language Model Outputs: Similarity, Diversity, and Bias","created":"2025-05-14","cited_by_count":10,"area":null},{"id":"2505.09757","title":"Trustless Autonomy: Understanding Motivations, Benefits, and Governance Dilemmas in Self-Sovereign Decentralized AI Agents","created":"2025-05-14","cited_by_count":10,"area":"agents"},{"id":"2509.02401","title":"Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning","created":"2025-09-02","cited_by_count":10,"area":"lr"},{"id":"2409.13642","title":"A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion","created":"2024-09-20","cited_by_count":9,"area":"agents"},{"id":"2410.12029","title":"On Classification with Large Language Models in Cultural Analytics","created":"2024-10-15","cited_by_count":9,"area":null},{"id":"2412.15304","title":"TinyLLM: A Framework for Training and Deploying Language Models at the Edge Computers","created":"2024-12-19","cited_by_count":9,"area":null},{"id":"2505.19240","title":"LLLMs: A Data-Driven Survey of Evolving Research on Limitations of Large Language Models","created":"2025-05-25","cited_by_count":9,"area":null},{"id":"2510.10390","title":"RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models","created":"2025-10-12","cited_by_count":9,"area":"rag"},{"id":"2511.01268","title":"Rescuing the Unpoisoned: Efficient Defense against Knowledge Corruption Attacks on RAG Systems","created":"2025-11-03","cited_by_count":9,"area":"rag"},{"id":"2511.09008","title":"A Neurosymbolic Approach to Natural Language Formalization and Verification","created":"2025-11-12","cited_by_count":9,"area":null},{"id":"2402.13547","title":"ThinkNote: Enhancing Knowledge Integration and Utilization of Large Language Models via Constructivist Cognition Modeling","created":"2024-02-21","cited_by_count":8,"area":"lr"},{"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":"2407.08642","title":"Towards Building Specialized Generalist AI with System 1 and System 2 Fusion","created":"2024-07-11","cited_by_count":8,"area":null},{"id":"2407.18069","title":"$\\text{C}^2\\text{P}$: Featuring Large Language Models with Causal Reasoning","created":"2024-07-25","cited_by_count":8,"area":"lr"},{"id":"2408.07004","title":"Casper: Prompt Sanitization for Protecting User Privacy in Web-Based Large Language Models","created":"2024-08-13","cited_by_count":8,"area":null},{"id":"2409.15454","title":"In-Context Learning May Not Elicit Trustworthy Reasoning: A-Not-B Errors in Pretrained Language Models","created":"2024-09-23","cited_by_count":8,"area":"lr"},{"id":"2503.01642","title":"Graph-Augmented Reasoning: Evolving Step-by-Step Knowledge Graph Retrieval for LLM Reasoning","created":"2025-03-03","cited_by_count":8,"area":"lr"},{"id":"2505.12833","title":"Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs","created":"2025-05-19","cited_by_count":8,"area":"lr"},{"id":"2506.10060","title":"Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems","created":"2025-06-11","cited_by_count":8,"area":null},{"id":"2404.01558","title":"Automated User Story Generation with Test Case Specification Using Large Language Model","created":"2024-04-02","cited_by_count":7,"area":null},{"id":"2404.09077","title":"CuriousLLM: Elevating Multi-Document Question Answering with LLM-Enhanced Knowledge Graph Reasoning","created":"2024-04-13","cited_by_count":7,"area":"lr"},{"id":"2404.16478","title":"Evaluating Consistency and Reasoning Capabilities of Large Language Models","created":"2024-04-25","cited_by_count":7,"area":"lr"},{"id":"2407.04485","title":"Leveraging Graph Structures to Detect Hallucinations in Large Language Models","created":"2024-07-05","cited_by_count":7,"area":null}],"next_cursor":"100"}