{"total":121,"rows":[{"id":"2401.01313","title":"A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models","created":"2024-01-02","cited_by_count":269,"area":null},{"id":"2406.15927","title":"Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs","created":"2024-06-22","cited_by_count":259,"area":null},{"id":"2410.02707","title":"LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations","created":"2024-10-03","cited_by_count":244,"area":null},{"id":"2405.05904","title":"Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?","created":"2024-05-09","cited_by_count":232,"area":null},{"id":"2509.04664","title":"Why Language Models Hallucinate","created":"2025-09-04","cited_by_count":220,"area":null},{"id":"2401.01286","title":"A Comprehensive Study of Knowledge Editing for Large Language Models","created":"2024-01-02","cited_by_count":163,"area":null},{"id":"2405.20003","title":"Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities","created":"2024-05-30","cited_by_count":159,"area":null},{"id":"2401.01301","title":"Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models","created":"2024-01-02","cited_by_count":150,"area":null},{"id":"2407.18370","title":"Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement","created":"2024-07-25","cited_by_count":105,"area":null},{"id":"2406.08391","title":"Large Language Models Must Be Taught to Know What They Don't Know","created":"2024-06-12","cited_by_count":100,"area":null},{"id":"2405.16908","title":"Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?","created":"2024-05-27","cited_by_count":87,"area":null},{"id":"2312.15710","title":"Alleviating Hallucinations of Large Language Models through Induced Hallucinations","created":"2023-12-25","cited_by_count":79,"area":null},{"id":"2402.02420","title":"Factuality of Large Language Models: A Survey","created":"2024-02-04","cited_by_count":66,"area":null},{"id":"2406.10279","title":"We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs","created":"2024-06-12","cited_by_count":65,"area":null},{"id":"2404.00213","title":"Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning","created":"2024-03-30","cited_by_count":58,"area":null},{"id":"2402.12847","title":"Instruction-tuned Language Models are Better Knowledge Learners","created":"2024-02-20","cited_by_count":55,"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":"2402.02713","title":"Position: What Can Large Language Models Tell Us about Time Series Analysis","created":"2024-02-05","cited_by_count":47,"area":null},{"id":"2311.09533","title":"Effective Large Language Model Adaptation for Improved Grounding and Citation Generation","created":"2023-11-16","cited_by_count":45,"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":"2311.09114","title":"Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification","created":"2023-11-15","cited_by_count":38,"area":null},{"id":"2504.04635","title":"Steering off Course: Reliability Challenges in Steering Language Models","created":"2025-04-06","cited_by_count":34,"area":null},{"id":"2402.06544","title":"Calibrating Long-form Generations from Large Language Models","created":"2024-02-09","cited_by_count":32,"area":null},{"id":"2406.10881","title":"Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals","created":"2024-06-16","cited_by_count":32,"area":null},{"id":"2410.22685","title":"Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings","created":"2024-10-30","cited_by_count":30,"area":null},{"id":"2501.06521","title":"Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering","created":"2025-01-11","cited_by_count":28,"area":null},{"id":"2503.10728","title":"DarkBench: Benchmarking Dark Patterns in Large Language Models","created":"2025-03-13","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":"2406.15718","title":"Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Models","created":"2024-06-22","cited_by_count":26,"area":null},{"id":"2312.02073","title":"A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia","created":"2023-12-04","cited_by_count":24,"area":null},{"id":"2406.11267","title":"Mitigating Large Language Model Hallucination with Faithful Finetuning","created":"2024-06-17","cited_by_count":24,"area":null},{"id":"2401.08574","title":"Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability","created":"2024-01-16","cited_by_count":22,"area":null},{"id":"2404.10315","title":"Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience","created":"2024-04-16","cited_by_count":21,"area":null},{"id":"2404.14986","title":"$\\texttt{MiniMol}$: A Parameter-Efficient Foundation Model for Molecular Learning","created":"2024-04-23","cited_by_count":20,"area":null},{"id":"2405.12701","title":"OLAPH: Improving Factuality in Biomedical Long-form Question Answering","created":"2024-05-21","cited_by_count":20,"area":null},{"id":"2406.07457","title":"Estimating the Hallucination Rate of Generative AI","created":"2024-06-11","cited_by_count":20,"area":null},{"id":"2502.19110","title":"Conformal Linguistic Calibration: Trading-off between Factuality and Specificity","created":"2025-02-26","cited_by_count":20,"area":null},{"id":"2404.09971","title":"Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs","created":"2024-04-15","cited_by_count":19,"area":null},{"id":"2408.12325","title":"Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators","created":"2024-08-22","cited_by_count":19,"area":null},{"id":"2410.14309","title":"LoGU: Long-form Generation with Uncertainty Expressions","created":"2024-10-18","cited_by_count":19,"area":null},{"id":"2402.11456","title":"FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence","created":"2024-02-18","cited_by_count":18,"area":null},{"id":"2407.03572","title":"Core: Robust Factual Precision with Informative Sub-Claim Identification","created":"2024-07-04","cited_by_count":16,"area":null},{"id":"2410.15821","title":"The effect of fine-tuning on language model toxicity","created":"2024-10-21","cited_by_count":16,"area":null},{"id":"2505.24858","title":"MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs","created":"2025-05-30","cited_by_count":16,"area":null},{"id":"2408.13808","title":"Towards Reliable Medical Question Answering: Techniques and Challenges in Mitigating Hallucinations in Language Models","created":"2024-08-25","cited_by_count":15,"area":null},{"id":"2410.18359","title":"Improving Model Factuality with Fine-grained Critique-based Evaluator","created":"2024-10-24","cited_by_count":15,"area":null},{"id":"2404.01295","title":"Towards Safety and Helpfulness Balanced Responses via Controllable Large Language Models","created":"2024-04-01","cited_by_count":14,"area":null},{"id":"2410.22071","title":"Distinguishing Ignorance from Error in LLM Hallucinations","created":"2024-10-29","cited_by_count":14,"area":null},{"id":"2406.13124","title":"Learning to Generate Answers with Citations via Factual Consistency Models","created":"2024-06-19","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":"2312.14335","title":"Context-aware Decoding Reduces Hallucination in Query-focused Summarization","created":"2023-12-21","cited_by_count":11,"area":null},{"id":"2401.02575","title":"Large Language Models for Social Networks: Applications, Challenges, and Solutions","created":"2024-01-04","cited_by_count":11,"area":null},{"id":"2402.11176","title":"KnowTuning: Knowledge-aware Fine-tuning for Large Language Models","created":"2024-02-17","cited_by_count":11,"area":null},{"id":"2402.13463","title":"RefuteBench: Evaluating Refuting Instruction-Following for Large Language Models","created":"2024-02-21","cited_by_count":11,"area":null},{"id":"2409.08435","title":"When Context Leads but Parametric Memory Follows in Large Language Models","created":"2024-09-13","cited_by_count":11,"area":null},{"id":"2410.17234","title":"Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy","created":"2024-10-22","cited_by_count":11,"area":null},{"id":"2401.16713","title":"Prospects for inconsistency detection using large language models and sheaves","created":"2024-01-30","cited_by_count":10,"area":null},{"id":"2402.12566","title":"GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence","created":"2024-02-19","cited_by_count":10,"area":null},{"id":"2403.19113","title":"FACTOID: FACtual enTailment fOr hallucInation Detection","created":"2024-03-28","cited_by_count":10,"area":null},{"id":"2404.00942","title":"Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs","created":"2024-04-01","cited_by_count":10,"area":null},{"id":"2412.00631","title":"ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning","created":"2024-12-01","cited_by_count":10,"area":null},{"id":"2505.23657","title":"Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation","created":"2025-05-29","cited_by_count":10,"area":null},{"id":"2402.17982","title":"Collaborative decoding of critical tokens for boosting factuality of large language models","created":"2024-02-28","cited_by_count":9,"area":null},{"id":"2403.14666","title":"SyllabusQA: A Course Logistics Question Answering Dataset","created":"2024-03-03","cited_by_count":9,"area":null},{"id":"2406.12221","title":"On-Policy Self-Alignment with Fine-grained Knowledge Feedback for Hallucination Mitigation","created":"2024-06-18","cited_by_count":9,"area":null},{"id":"2502.15419","title":"Beyond Translation: LLM-Based Data Generation for Multilingual Fact-Checking","created":"2025-02-21","cited_by_count":8,"area":null},{"id":"2510.12839","title":"FaStfact: Faster, Stronger Long-Form Factuality Evaluations in LLMs","created":"2025-10-13","cited_by_count":8,"area":null},{"id":"2502.03199","title":"Improve Decoding Factuality by Token-wise Cross Layer Entropy of Large Language Models","created":"2025-02-05","cited_by_count":7,"area":null},{"id":"2402.15422","title":"A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models","created":"2024-02-23","cited_by_count":6,"area":null},{"id":"2405.13022","title":"LLMs can learn self-restraint through iterative self-reflection","created":"2024-05-15","cited_by_count":6,"area":null},{"id":"2503.22746","title":"Susceptibility of Large Language Models to User-Driven Factors in Medical Queries","created":"2025-03-26","cited_by_count":6,"area":null},{"id":"2504.19622","title":"From Evidence to Belief: A Bayesian Epistemology Approach to Language Models","created":"2025-04-28","cited_by_count":6,"area":null},{"id":"2402.09147","title":"Into the Unknown: Self-Learning Large Language Models","created":"2024-02-14","cited_by_count":5,"area":null},{"id":"2506.11111","title":"Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions","created":"2025-06-08","cited_by_count":5,"area":null},{"id":"2601.05062","title":"Compositional Steering of Large Language Models with Steering Tokens","created":"2026-01-08","cited_by_count":5,"area":null},{"id":"2603.19532","title":"EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Models","created":"2026-03-20","cited_by_count":5,"area":null},{"id":"2605.01428","title":"Hallucinations Undermine Trust; Metacognition is a Way Forward","created":"2026-05-02","cited_by_count":5,"area":null},{"id":"2405.16579","title":"Automatically Generating Numerous Context-Driven SFT Data for LLMs across Diverse Granularity","created":"2024-05-26","cited_by_count":4,"area":null},{"id":"2406.14434","title":"Selected Languages are All You Need for Cross-lingual Truthfulness Transfer","created":"2024-06-20","cited_by_count":4,"area":null},{"id":"2407.11930","title":"Localizing and Mitigating Errors in Long-form Question Answering","created":"2024-07-16","cited_by_count":4,"area":null},{"id":"2502.19127","title":"Exploring the Generalizability of Factual Hallucination Mitigation via Enhancing Precise Knowledge Utilization","created":"2025-02-26","cited_by_count":4,"area":null},{"id":"2511.12236","title":"Consistency Is the Key: Detecting Hallucinations in LLM Generated Text By Checking Inconsistencies About Key Facts","created":"2025-11-15","cited_by_count":4,"area":null},{"id":"2407.00365","title":"Financial Knowledge Large Language Model","created":"2024-06-29","cited_by_count":3,"area":null},{"id":"2410.09629","title":"Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models","created":"2024-10-12","cited_by_count":3,"area":null},{"id":"2507.19586","title":"Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning","created":"2025-07-25","cited_by_count":3,"area":null},{"id":"2508.15213","title":"Select to Know: An Internal-External Knowledge Self-Selection Framework for Domain-Specific Question Answering","created":"2025-08-21","cited_by_count":3,"area":null},{"id":"2602.20696","title":"PromptCD: Test-Time Behavior Enhancement via Polarity-Prompt Contrastive Decoding","created":"2026-02-24","cited_by_count":3,"area":null},{"id":"2404.08727","title":"Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases","created":"2024-04-12","cited_by_count":2,"area":null},{"id":"2404.16532","title":"Global Concept Explanations for Graphs by Contrastive Learning","created":"2024-04-25","cited_by_count":2,"area":null},{"id":"2506.04051","title":"High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning","created":"2025-06-04","cited_by_count":2,"area":null},{"id":"2602.11166","title":"Small Updates, Big Doubts: Does Parameter-Efficient Fine-tuning Enhance Hallucination Detection ?","created":"2026-01-17","cited_by_count":2,"area":null},{"id":"2603.20276","title":"Me, Myself, and $\\pi$ : Evaluating and Explaining LLM Introspection","created":"2026-03-17","cited_by_count":2,"area":null},{"id":"2605.28778","title":"Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence?","created":"2026-05-27","cited_by_count":2,"area":null},{"id":"2407.13048","title":"Establishing Knowledge Preference in Language Models","created":"2024-07-17","cited_by_count":1,"area":null},{"id":"2410.23526","title":"LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models","created":"2024-10-31","cited_by_count":1,"area":null},{"id":"2411.03300","title":"VERITAS: A Unified Approach to Reliability Evaluation","created":"2024-11-05","cited_by_count":1,"area":null},{"id":"2502.13648","title":"UniKnow: A Unified Framework for Reliable Language Model Behavior across Parametric and External Knowledge","created":"2025-02-19","cited_by_count":1,"area":null},{"id":"2503.01131","title":"Beyond QA Pairs: Assessing Parameter-Efficient Fine-Tuning for Fact Embedding in LLMs","created":"2025-03-03","cited_by_count":1,"area":null},{"id":"2503.10676","title":"Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data","created":"2025-03-10","cited_by_count":1,"area":null},{"id":"2504.03302","title":"Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models","created":"2025-04-04","cited_by_count":1,"area":null}],"next_cursor":"100"}