{"total":283,"rows":[{"id":"2507.05257","title":"Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions","created":"2025-07-07","cited_by_count":254,"area":"agents"},{"id":"2404.07103","title":"Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs","created":"2024-04-10","cited_by_count":119,"area":"lr"},{"id":"2408.10343","title":"LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain","created":"2024-08-19","cited_by_count":118,"area":"rag"},{"id":"2410.11414","title":"ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability","created":"2024-10-15","cited_by_count":101,"area":"rag"},{"id":"2410.13085","title":"MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models","created":"2024-10-16","cited_by_count":85,"area":"mllm"},{"id":"2407.10817","title":"Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation","created":"2024-07-15","cited_by_count":74,"area":null},{"id":"2411.06037","title":"Sufficient Context: A New Lens on Retrieval Augmented Generation Systems","created":"2024-11-09","cited_by_count":72,"area":"rag"},{"id":"2502.12289","title":"Evaluating Step-by-step Reasoning Traces: A Survey","created":"2025-02-17","cited_by_count":63,"area":"lr"},{"id":"2407.08488","title":"Lynx: An Open Source Hallucination Evaluation Model","created":"2024-07-11","cited_by_count":57,"area":"rag"},{"id":"2501.05874","title":"VideoRAG: Retrieval-Augmented Generation over Video Corpus","created":"2025-01-10","cited_by_count":57,"area":"rag"},{"id":"2501.03468","title":"MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems","created":"2025-01-07","cited_by_count":51,"area":"rag"},{"id":"2510.06265","title":"Large Language Models Hallucination: A Comprehensive Survey","created":"2025-10-05","cited_by_count":49,"area":null},{"id":"2410.04585","title":"Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval","created":"2024-10-06","cited_by_count":45,"area":"lr"},{"id":"2408.01262","title":"RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework","created":"2024-08-02","cited_by_count":39,"area":"rag"},{"id":"2606.04990","title":"From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents","created":"2026-06-03","cited_by_count":37,"area":"agents"},{"id":"2502.17125","title":"LettuceDetect: A Hallucination Detection Framework for RAG Applications","created":"2025-02-24","cited_by_count":34,"area":"rag"},{"id":"2409.14664","title":"Direct Judgement Preference Optimization","created":"2024-09-23","cited_by_count":33,"area":"alignment"},{"id":"2410.21943","title":"Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial Applications","created":"2024-10-29","cited_by_count":31,"area":"rag"},{"id":"2504.11975","title":"SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared Task on Hallucinations and Related Observable Overgeneration Mistakes","created":"2025-04-16","cited_by_count":27,"area":null},{"id":"2506.00054","title":"Retrieval-Augmented Generation: A Comprehensive Survey of Architectures, Enhancements, and Robustness Frontiers","created":"2025-05-28","cited_by_count":27,"area":"rag"},{"id":"2509.09660","title":"Steering MoE LLMs via Expert (De)Activation","created":"2025-09-11","cited_by_count":26,"area":"moe"},{"id":"2503.23895","title":"Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement","created":"2025-03-31","cited_by_count":25,"area":"rag"},{"id":"2410.13210","title":"FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMs","created":"2024-10-17","cited_by_count":24,"area":"rag"},{"id":"2503.15620","title":"Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings","created":"2025-03-19","cited_by_count":24,"area":null},{"id":"2505.04847","title":"Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards","created":"2025-05-07","cited_by_count":20,"area":"rag"},{"id":"2504.10063","title":"Hallucination Detection in LLMs with Topological Divergence on Attention Graphs","created":"2025-04-14","cited_by_count":19,"area":null},{"id":"2412.12004","title":"The Open Source Advantage in Large Language Models (LLMs)","created":"2024-12-16","cited_by_count":18,"area":null},{"id":"2506.07671","title":"GaRAGe: A Benchmark with Grounding Annotations for RAG Evaluation","created":"2025-06-09","cited_by_count":18,"area":null},{"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":"2507.21017","title":"MIRAGE-Bench: LLM Agent is Hallucinating and Where to Find Them","created":"2025-07-28","cited_by_count":16,"area":"agents"},{"id":"2601.06818","title":"AgentHallu: Benchmarking Automated Hallucination Attribution of LLM-based Agents","created":"2026-01-11","cited_by_count":16,"area":"agents"},{"id":"2604.07223","title":"TraceSafe: A Systematic Assessment of LLM Guardrails on Multi-Step Tool-Calling Trajectories","created":"2026-04-08","cited_by_count":16,"area":"agents"},{"id":"2407.06992","title":"Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective","created":"2024-07-09","cited_by_count":15,"area":null},{"id":"2410.04734","title":"TLDR: Token-Level Detective Reward Model for Large Vision Language Models","created":"2024-10-07","cited_by_count":15,"area":"mllm"},{"id":"2410.18359","title":"Improving Model Factuality with Fine-grained Critique-based Evaluator","created":"2024-10-24","cited_by_count":15,"area":null},{"id":"2502.07184","title":"Refine Knowledge of Large Language Models via Adaptive Contrastive Learning","created":"2025-02-11","cited_by_count":15,"area":null},{"id":"2504.13128","title":"FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents","created":"2025-04-17","cited_by_count":15,"area":null},{"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":"2407.12943","title":"Halu-J: Critique-Based Hallucination Judge","created":"2024-07-17","cited_by_count":14,"area":null},{"id":"2410.13716","title":"MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems","created":"2024-10-17","cited_by_count":14,"area":"rag"},{"id":"2501.17144","title":"FactCG: Enhancing Fact Checkers with Graph-Based Multi-Hop Data","created":"2025-01-28","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":"2504.07069","title":"HalluciNot: Hallucination Detection Through Context and Common Knowledge Verification","created":"2025-04-09","cited_by_count":13,"area":null},{"id":"2506.13342","title":"Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifiers","created":"2025-06-16","cited_by_count":13,"area":null},{"id":"2402.05359","title":"An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models","created":"2024-02-08","cited_by_count":12,"area":null},{"id":"2406.09818","title":"ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures","created":"2024-06-14","cited_by_count":12,"area":"rag"},{"id":"2411.16638","title":"Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation","created":"2024-11-25","cited_by_count":11,"area":null},{"id":"2501.06582","title":"ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting","created":"2025-01-11","cited_by_count":11,"area":null},{"id":"2412.17056","title":"The HalluRAG Dataset: Detecting Closed-Domain Hallucinations in RAG Applications Using an LLM's Internal States","created":"2024-12-22","cited_by_count":10,"area":null},{"id":"2506.08354","title":"Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning","created":"2025-06-10","cited_by_count":10,"area":null},{"id":"2508.08287","title":"Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions","created":"2025-08-04","cited_by_count":10,"area":null},{"id":"2605.19196","title":"Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?","created":"2026-05-18","cited_by_count":10,"area":"agents"},{"id":"2507.14239","title":"CCL-XCoT: An Efficient Cross-Lingual Knowledge Transfer Method for Mitigating Hallucination Generation","created":"2025-07-17","cited_by_count":9,"area":null},{"id":"2509.21875","title":"LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals","created":"2025-09-26","cited_by_count":9,"area":"rag"},{"id":"2608.05179","title":"Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap","created":"2026-06-29","cited_by_count":9,"area":"agents"},{"id":"2501.14883","title":"Verify with Caution: The Pitfalls of Relying on Imperfect Factuality Metrics","created":"2025-01-24","cited_by_count":8,"area":null},{"id":"2503.07158","title":"Generative AI in Transportation Planning: A Survey","created":"2025-03-10","cited_by_count":8,"area":null},{"id":"2506.20978","title":"Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality","created":"2025-06-26","cited_by_count":8,"area":"rag"},{"id":"2508.05201","title":"FAITH: A Framework for Assessing Intrinsic Tabular Hallucinations in Finance","created":"2025-08-07","cited_by_count":8,"area":null},{"id":"2510.13193","title":"ReMindRAG: Low-Cost LLM-Guided Knowledge Graph Traversal for Efficient RAG","created":"2025-10-15","cited_by_count":8,"area":"rag"},{"id":"2602.02888","title":"HALT: Hallucination Assessment via Log-probs as Time series","created":"2026-02-02","cited_by_count":8,"area":null},{"id":"2605.03534","title":"SURE-RAG: Sufficiency and Uncertainty-Aware Evidence Verification for Selective Retrieval-Augmented Generation","created":"2026-05-05","cited_by_count":8,"area":"rag"},{"id":"2609.29429","title":"Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures","created":"2026-09-24","cited_by_count":8,"area":"safety"},{"id":"2404.12041","title":"A Survey of Automatic Hallucination Evaluation on Natural Language Generation","created":"2024-04-18","cited_by_count":7,"area":null},{"id":"2502.17611","title":"Evaluating the Effect of Retrieval Augmentation on Social Biases","created":"2025-02-24","cited_by_count":7,"area":"rag"},{"id":"2504.10198","title":"DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation","created":"2025-04-14","cited_by_count":7,"area":"rag"},{"id":"2507.02870","title":"Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models","created":"2025-06-06","cited_by_count":7,"area":null},{"id":"2512.08892","title":"Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders","created":"2025-12-09","cited_by_count":7,"area":"rag"},{"id":"2605.17830","title":"Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents","created":"2026-05-18","cited_by_count":7,"area":"agents"},{"id":"2406.13692","title":"Synchronous Faithfulness Monitoring for Trustworthy Retrieval-Augmented Generation","created":"2024-06-19","cited_by_count":6,"area":"rag"},{"id":"2406.17095","title":"Attention Instruction: Amplifying Attention in the Middle via Prompting","created":"2024-06-24","cited_by_count":6,"area":null},{"id":"2411.07688","title":"ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAG","created":"2024-11-12","cited_by_count":6,"area":null},{"id":"2503.10690","title":"Battling Misinformation: An Empirical Study on Adversarial Factuality in Open-Source Large Language Models","created":"2025-03-12","cited_by_count":6,"area":null},{"id":"2504.04335","title":"Hallucinated Span Detection with Multi-View Attention Features","created":"2025-04-06","cited_by_count":6,"area":null},{"id":"2505.21072","title":"Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation","created":"2025-05-27","cited_by_count":6,"area":"rag"},{"id":"2511.17908","title":"Principled Context Engineering for RAG: Statistical Guarantees via Conformal Prediction","created":"2025-11-22","cited_by_count":6,"area":"rag"},{"id":"2601.05866","title":"FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG","created":"2026-01-09","cited_by_count":6,"area":"rag"},{"id":"2606.22737","title":"GroundEval: A Deterministic Replacement for LLM-as-Judge in Stateful Agent Evaluation","created":"2026-06-22","cited_by_count":6,"area":"agents"},{"id":"2406.00975","title":"Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High Accuracy and Low Cost","created":"2024-06-03","cited_by_count":5,"area":null},{"id":"2412.11404","title":"Attention with Dependency Parsing Augmentation for Fine-Grained Attribution","created":"2024-12-16","cited_by_count":5,"area":null},{"id":"2501.13264","title":"OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation","created":"2025-01-22","cited_by_count":5,"area":"alignment"},{"id":"2504.01840","title":"LRAGE: Legal Retrieval Augmented Generation Evaluation Tool","created":"2025-04-02","cited_by_count":5,"area":"rag"},{"id":"2504.05324","title":"Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysis","created":"2025-02-28","cited_by_count":5,"area":null},{"id":"2508.06361","title":"Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts","created":"2025-08-08","cited_by_count":5,"area":"lr"},{"id":"2508.19720","title":"Continuously Steering LLMs Sensitivity to Contextual Knowledge with Proxy Models","created":"2025-08-27","cited_by_count":5,"area":null},{"id":"2602.06616","title":"Confundo: Learning to Generate Robust Poison for Practical RAG Systems","created":"2026-02-06","cited_by_count":5,"area":"rag"},{"id":"2603.24579","title":"MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination","created":"2026-03-25","cited_by_count":5,"area":"rag"},{"id":"2606.30306","title":"Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents","created":"2026-06-29","cited_by_count":5,"area":null},{"id":"2608.28945","title":"Automated Researchers Can Mitigate Well-characterized Alignment Failures","created":"2026-08-28","cited_by_count":5,"area":null},{"id":"2408.12748","title":"SLM Meets LLM: Balancing Latency, Interpretability and Consistency in Hallucination Detection","created":"2024-08-22","cited_by_count":4,"area":null},{"id":"2409.11353","title":"THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models","created":"2024-09-17","cited_by_count":4,"area":null},{"id":"2505.13506","title":"EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation","created":"2025-05-16","cited_by_count":4,"area":"rag"},{"id":"2507.20836","title":"First Hallucination Tokens Are Different from Conditional Ones","created":"2025-07-28","cited_by_count":4,"area":null},{"id":"2509.19372","title":"Representation-based Broad Hallucination Detectors Fail to Generalize Out of Distribution","created":"2025-09-19","cited_by_count":4,"area":null},{"id":"2510.06354","title":"LLM Bias Detection and Mitigation through the Lens of Desired Distributions","created":"2025-10-07","cited_by_count":4,"area":null},{"id":"2602.01405","title":"Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agents","created":"2026-02-01","cited_by_count":4,"area":"agents"},{"id":"2605.12213","title":"Goal-Oriented Reasoning for RAG-based Memory in Conversational Agentic LLM Systems","created":"2026-05-12","cited_by_count":4,"area":"lr"},{"id":"2608.01021","title":"Can Humans Dream of Electric Sheep? Human-Written Samples for Fine-Grained Vision-and-Language Hallucination Benchmarking","created":"2026-08-02","cited_by_count":4,"area":null},{"id":"2406.14162","title":"DIRAS: Efficient LLM Annotation of Document Relevance in Retrieval Augmented Generation","created":"2024-06-20","cited_by_count":3,"area":"rag"},{"id":"2412.05447","title":"TOBUGraph: Knowledge Graph-Based Retrieval for Enhanced LLM Performance Beyond RAG","created":"2024-12-06","cited_by_count":3,"area":"rag"}],"next_cursor":"100"}