{"total":41,"rows":[{"id":"2311.05232","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","created":"2023-11-09","cited_by_count":1601,"area":null},{"id":"2403.08319","title":"Knowledge Conflicts for LLMs: A Survey","created":"2024-03-13","cited_by_count":283,"area":null},{"id":"2311.08298","title":"A Survey of Confidence Estimation and Calibration in Large Language Models","created":"2023-11-14","cited_by_count":256,"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":"2406.02543","title":"To Believe or Not to Believe Your LLM","created":"2024-06-04","cited_by_count":120,"area":null},{"id":"2401.13275","title":"Can AI Assistants Know What They Don't Know?","created":"2024-01-24","cited_by_count":50,"area":null},{"id":"2412.12472","title":"Knowledge Boundary of Large Language Models: A Survey","created":"2024-12-17","cited_by_count":40,"area":null},{"id":"2406.07070","title":"HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination Evaluation","created":"2024-06-11","cited_by_count":27,"area":null},{"id":"2406.11278","title":"Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs","created":"2024-06-17","cited_by_count":23,"area":null},{"id":"2405.14383","title":"Perception of Knowledge Boundary for Large Language Models through Semi-open-ended Question Answering","created":"2024-05-23","cited_by_count":20,"area":null},{"id":"2311.01555","title":"Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers","created":"2023-11-02","cited_by_count":19,"area":null},{"id":"2403.00896","title":"DiaHalu: A Dialogue-level Hallucination Evaluation Benchmark for Large Language Models","created":"2024-03-01","cited_by_count":15,"area":null},{"id":"2502.19573","title":"Do Large Language Models Know How Much They Know?","created":"2025-02-26","cited_by_count":11,"area":null},{"id":"2510.12040","title":"Uncertainty Quantification for Hallucination Detection in Large Language Models: Foundations, Methodology, and Future Directions","created":"2025-10-14","cited_by_count":11,"area":null},{"id":"2510.09033","title":"Do LLMs Really Know What They Don't Know? Internal States Mainly Reflect Knowledge Recall Rather Than Truthfulness","created":"2025-10-10","cited_by_count":10,"area":null},{"id":"2501.02020","title":"Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection","created":"2025-01-02","cited_by_count":8,"area":null},{"id":"2506.10060","title":"Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems","created":"2025-06-11","cited_by_count":8,"area":null},{"id":"2406.18326","title":"PaCoST: Paired Confidence Significance Testing for Benchmark Contamination Detection in Large Language Models","created":"2024-06-26","cited_by_count":6,"area":null},{"id":"2505.13406","title":"AutoMathKG: The automated mathematical knowledge graph based on LLM and vector database","created":"2025-05-19","cited_by_count":6,"area":null},{"id":"2601.09445","title":"Where Knowledge Collides: A Mechanistic Study of Intra-Memory Knowledge Conflict in Language Models","created":"2026-01-14","cited_by_count":5,"area":null},{"id":"2410.14405","title":"Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion","created":"2024-10-18","cited_by_count":4,"area":null},{"id":"2504.18346","title":"Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review","created":"2025-04-25","cited_by_count":4,"area":null},{"id":"2507.08203","title":"TruthTorchLM: A Comprehensive Library for Predicting Truthfulness in LLM Outputs","created":"2025-07-10","cited_by_count":4,"area":null},{"id":"2409.16913","title":"Tell Me What You Don't Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing","created":"2024-09-25","cited_by_count":3,"area":null},{"id":"2411.11266","title":"VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs","created":"2024-11-18","cited_by_count":3,"area":null},{"id":"2504.16871","title":"Exploring How LLMs Capture and Represent Domain-Specific Knowledge","created":"2025-04-23","cited_by_count":3,"area":null},{"id":"2412.15683","title":"Variability Need Not Imply Error: The Case of Adequate but Semantically Distinct Responses","created":"2024-12-20","cited_by_count":2,"area":null},{"id":"2504.08300","title":"Large Language Models Could Be Rote Learners","created":"2025-04-11","cited_by_count":2,"area":null},{"id":"2504.19472","title":"Conflicts in Texts: Data, Implications and Challenges","created":"2025-04-28","cited_by_count":2,"area":null},{"id":"2505.13545","title":"Know Or Not: a library for evaluating out-of-knowledge base robustness","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2510.19172","title":"When Facts Change: Probing LLMs on Evolving Knowledge with evolveQA","created":"2025-10-22","cited_by_count":2,"area":null},{"id":"2505.21958","title":"Resolving Knowledge Conflicts in Domain-specific Data Selection: A Case Study on Medical Instruction-tuning","created":"2025-05-28","cited_by_count":1,"area":null},{"id":"2511.08916","title":"HalluClean: A Unified Framework to Combat Hallucinations in LLMs","created":"2025-11-12","cited_by_count":1,"area":null},{"id":"2602.04853","title":"Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say \"I Don't Know\"","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2602.14065","title":"REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment","created":"2026-02-15","cited_by_count":1,"area":null},{"id":"2604.26139","title":"HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models","created":"2026-04-28","cited_by_count":1,"area":null},{"id":"2408.13073","title":"IntelliCare: Improving Healthcare Analysis with Variance-Controlled Patient-Level Knowledge from Large Language Models","created":"2024-08-23","cited_by_count":0,"area":null},{"id":"2412.11536","title":"Let your LLM generate a few tokens and you will reduce the need for retrieval","created":"2024-12-16","cited_by_count":0,"area":null},{"id":"2510.10539","title":"Detecting Hallucinations in Authentic LLM-Human Interactions","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2608.13484","title":"Toward a Gricean Retreat: Probing LLMs for Knowledge Boundaries and Referent Specificity","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2609.01687","title":"Learning Evidence Sufficiency Boundaries for Selective Answering in Grounded Multi-Hop QA","created":"2026-09-01","cited_by_count":0,"area":null}],"next_cursor":null}