{"total":67,"rows":[{"id":"2406.07496","title":"TextGrad: Automatic \"Differentiation\" via Text","created":"2024-06-11","cited_by_count":273,"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":"2411.16724","title":"Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens","created":"2024-11-23","cited_by_count":143,"area":"mllm"},{"id":"2411.14257","title":"Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models","created":"2024-11-21","cited_by_count":115,"area":"mechinterp"},{"id":"2401.03205","title":"The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models","created":"2024-01-06","cited_by_count":88,"area":null},{"id":"2404.17140","title":"Small Language Models Need Strong Verifiers to Self-Correct Reasoning","created":"2024-04-26","cited_by_count":86,"area":"lr"},{"id":"2405.00208","title":"A Primer on the Inner Workings of Transformer-based Language Models","created":"2024-04-30","cited_by_count":85,"area":null},{"id":"2312.17249","title":"Do Androids Know They're Only Dreaming of Electric Sheep?","created":"2023-12-28","cited_by_count":67,"area":"mechinterp"},{"id":"2405.17969","title":"Knowledge Circuits in Pretrained Transformers","created":"2024-05-28","cited_by_count":60,"area":"mechinterp"},{"id":"2406.04236","title":"Understanding Information Storage and Transfer in Multi-modal Large Language Models","created":"2024-06-06","cited_by_count":49,"area":"mllm"},{"id":"2403.01548","title":"In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation","created":"2024-03-03","cited_by_count":45,"area":null},{"id":"2403.20009","title":"On Large Language Models' Hallucination with Regard to Known Facts","created":"2024-03-29","cited_by_count":43,"area":null},{"id":"2406.12673","title":"Estimating Knowledge in Large Language Models Without Generating a Single Token","created":"2024-06-18","cited_by_count":40,"area":null},{"id":"2403.18167","title":"Mechanistic Understanding and Mitigation of Language Model Non-Factual Hallucinations","created":"2024-03-27","cited_by_count":38,"area":null},{"id":"2406.14785","title":"Understanding Finetuning for Factual Knowledge Extraction","created":"2024-06-20","cited_by_count":32,"area":null},{"id":"2404.19543","title":"RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing","created":"2024-04-30","cited_by_count":25,"area":"rag"},{"id":"2410.18860","title":"DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations","created":"2024-10-24","cited_by_count":25,"area":null},{"id":"2505.08200","title":"A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs","created":"2025-05-13","cited_by_count":21,"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":"2504.07863","title":"Robust Hallucination Detection in LLMs via Adaptive Token Selection","created":"2025-04-10","cited_by_count":19,"area":null},{"id":"2505.24630","title":"Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models","created":"2025-05-30","cited_by_count":19,"area":"lr"},{"id":"2402.07179","title":"Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models","created":"2024-02-11","cited_by_count":18,"area":"rag"},{"id":"2409.10566","title":"Eureka: Evaluating and Understanding Large Foundation Models","created":"2024-09-13","cited_by_count":18,"area":null},{"id":"2502.08767","title":"SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence","created":"2025-02-12","cited_by_count":18,"area":null},{"id":"2507.12379","title":"Probing for Arithmetic Errors in Language Models","created":"2025-07-16","cited_by_count":18,"area":null},{"id":"2501.12934","title":"Correctness Assessment of Code Generated by Large Language Models Using Internal Representations","created":"2025-01-22","cited_by_count":17,"area":null},{"id":"2510.00296","title":"Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT","created":"2025-09-30","cited_by_count":17,"area":null},{"id":"2501.09997","title":"Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models","created":"2025-01-17","cited_by_count":16,"area":"lr"},{"id":"2505.20045","title":"Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads","created":"2025-05-26","cited_by_count":16,"area":null},{"id":"2405.03205","title":"Anchored Answers: Unravelling Positional Bias in GPT-2's Multiple-Choice Questions","created":"2024-05-06","cited_by_count":15,"area":"mechinterp"},{"id":"2410.22071","title":"Distinguishing Ignorance from Error in LLM Hallucinations","created":"2024-10-29","cited_by_count":14,"area":null},{"id":"2505.16415","title":"Attributing Response to Context: A Jensen-Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation","created":"2025-05-22","cited_by_count":12,"area":"rag"},{"id":"2310.15511","title":"KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval","created":"2023-10-24","cited_by_count":11,"area":null},{"id":"2510.04013","title":"LLM Microscope: What Model Internals Reveal About Answer Correctness and Context Utilization","created":"2025-10-05","cited_by_count":11,"area":null},{"id":"2502.02173","title":"Mass-Editing Memory with Attention in Transformers: A cross-lingual exploration of knowledge","created":"2025-02-04","cited_by_count":10,"area":null},{"id":"2506.05451","title":"Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety","created":"2025-06-05","cited_by_count":10,"area":"safety"},{"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":"2402.19103","title":"Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models","created":"2024-02-29","cited_by_count":9,"area":null},{"id":"2409.11283","title":"Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling","created":"2024-09-17","cited_by_count":9,"area":null},{"id":"2410.22584","title":"BenchAgents: Multi-Agent Systems for Structured Benchmark Creation","created":"2024-10-29","cited_by_count":9,"area":"agents"},{"id":"2507.23221","title":"A Single Direction of Truth: An Observer Model's Linear Residual Probe Exposes and Steers Contextual Hallucinations","created":"2025-07-31","cited_by_count":9,"area":null},{"id":"2510.10494","title":"Tracing the Traces: Latent Temporal Signals for Efficient and Accurate Reasoning","created":"2025-10-12","cited_by_count":9,"area":"lr"},{"id":"2502.13329","title":"Language Models Can Predict Their Own Behavior","created":"2025-02-18","cited_by_count":8,"area":"lr"},{"id":"2410.22517","title":"Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models","created":"2024-10-29","cited_by_count":6,"area":null},{"id":"2505.16170","title":"When Do LLMs Admit Their Mistakes? Understanding The Role Of Model Belief In Retraction","created":"2025-05-22","cited_by_count":6,"area":null},{"id":"2505.17537","title":"Popular but Wrong: Understanding and Mitigating LLM Overconfidence through Knowledge Popularity","created":"2025-05-23","cited_by_count":6,"area":null},{"id":"2505.18524","title":"metaTextGrad: Automatically optimizing language model optimizers","created":"2025-05-24","cited_by_count":6,"area":null},{"id":"2509.24770","title":"Neural Message-Passing on Attention Graphs for Hallucination Detection","created":"2025-09-29","cited_by_count":6,"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":"2603.10384","title":"Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability","created":"2026-03-11","cited_by_count":5,"area":"lr"},{"id":"2604.16430","title":"HalluSAE: Detecting Hallucinations in Large Language Models via Sparse Auto-Encoders","created":"2026-04-06","cited_by_count":5,"area":"mechinterp"},{"id":"2509.09700","title":"Cross-Layer Attention Probing for Fine-Grained Hallucination Detection","created":"2025-09-04","cited_by_count":4,"area":null},{"id":"2510.15551","title":"Rethinking Cross-lingual Gaps from a Statistical Viewpoint","created":"2025-10-17","cited_by_count":4,"area":"lr"},{"id":"2502.13622","title":"REFIND at SemEval-2025 Task 3: Retrieval-Augmented Factuality Hallucination Detection in Large Language Models","created":"2025-02-19","cited_by_count":3,"area":"rag"},{"id":"2409.17954","title":"Enhancing elusive clues in knowledge learning by contrasting attention of language models","created":"2024-09-26","cited_by_count":2,"area":null},{"id":"2502.13490","title":"What are Models Thinking about? Understanding Large Language Model Hallucinations \"Psychology\" through Model Inner State Analysis","created":"2025-02-19","cited_by_count":2,"area":"lr"},{"id":"2503.14797","title":"FACTS&EVIDENCE: An Interactive Tool for Transparent Fine-Grained Factual Verification of Machine-Generated Text","created":"2025-03-19","cited_by_count":2,"area":null},{"id":"2505.24232","title":"From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models","created":"2025-05-30","cited_by_count":2,"area":"safety"},{"id":"2605.24024","title":"Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating","created":"2026-05-20","cited_by_count":2,"area":"mllm"},{"id":"2403.08739","title":"The Garden of Forking Paths: Observing Dynamic Parameters Distribution in Large Language Models","created":"2024-03-13","cited_by_count":1,"area":null},{"id":"2409.14371","title":"The Ability of Large Language Models to Evaluate Constraint-satisfaction in Agent Responses to Open-ended Requests","created":"2024-09-22","cited_by_count":1,"area":"agents"},{"id":"2407.10657","title":"An Empirical Study of Validating Synthetic Data for Formula Generation","created":"2024-07-15","cited_by_count":0,"area":"synth"},{"id":"2509.17932","title":"Training-free Truthfulness Detection via Sparse MLP Value Vectors","created":"2025-09-22","cited_by_count":0,"area":null},{"id":"2512.23837","title":"Adversarial Lens: Exploiting Attention Layers to Generate Adversarial Examples for Evaluation","created":"2025-12-29","cited_by_count":0,"area":"mechinterp"},{"id":"2604.22565","title":"Learning Evidence Highlighting for Frozen LLMs","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2608.11138","title":"Attention-Path Fragility as an Uncertainty Signal in Large Language Models","created":"2026-08-11","cited_by_count":0,"area":null},{"id":"2609.36813","title":"RESCUE: Repairing Language Model Errors to Sparse Circuits via Reinforcement Learning","created":"2026-09-29","cited_by_count":0,"area":"mechinterp"}],"next_cursor":null}