{"total":15,"rows":[{"id":"2502.14829","title":"Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps","created":"2025-02-20","cited_by_count":47,"area":"lr"},{"id":"2505.17406","title":"Robust Answers, Fragile Logic: Probing the Decoupling Hypothesis in LLM Reasoning","created":"2025-05-23","cited_by_count":11,"area":"lr"},{"id":"2504.05294","title":"Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations","created":"2025-04-07","cited_by_count":9,"area":"lr"},{"id":"2510.24236","title":"Towards Transparent Reasoning: What Drives Faithfulness in Large Language Models?","created":"2025-10-28","cited_by_count":5,"area":"lr"},{"id":"2506.19492","title":"Is Long-to-Short a Free Lunch? Investigating Inconsistency and Reasoning Efficiency in LRMs","created":"2025-06-24","cited_by_count":2,"area":"lr"},{"id":"2510.14014","title":"CRaFT: An Explanation-Based Framework for Evaluating Cultural Reasoning in Multilingual Language Models","created":"2025-10-15","cited_by_count":2,"area":"lr"},{"id":"2602.09832","title":"LLM Reasoning Predicts When Models Are Right: Evidence from Coding Classroom Discourse","created":"2026-02-10","cited_by_count":2,"area":"lr"},{"id":"2603.13988","title":"Faithful or Just Plausible? Evaluating the Faithfulness of Closed-Source LLMs in Medical Reasoning","created":"2026-03-14","cited_by_count":2,"area":"lr"},{"id":"2410.13216","title":"Anchored Alignment for Self-Explanations Enhancement","created":"2024-10-17","cited_by_count":1,"area":"lr"},{"id":"2509.22363","title":"Investigating Faithfulness in Large Audio Language Models","created":"2025-09-26","cited_by_count":1,"area":"lr"},{"id":"2602.22583","title":"Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance","created":"2026-02-26","cited_by_count":1,"area":"lr"},{"id":"2602.14002","title":"The Sufficiency-Conciseness Trade-off in LLM Self-Explanation from an Information Bottleneck Perspective","created":"2026-02-15","cited_by_count":0,"area":"lr"},{"id":"2604.14641","title":"Learning to Draw ASCII Improves Spatial Reasoning in Language Models","created":"2026-04-16","cited_by_count":0,"area":"lr"},{"id":"2604.17301","title":"RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation","created":"2026-04-19","cited_by_count":0,"area":"lr"},{"id":"2606.28615","title":"What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs","created":"2026-06-26","cited_by_count":0,"area":"lr"}],"next_cursor":null}