How the Audit Rule Shapes Faithful Factor Explanations in LLMs

arXiv:2610.01514 · cs.CL · Submitted 2026-10-01 · Read on arXiv

cs.CL

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Verification — 51× in this paper · explained in 2 episodes
• Verifier — 20× in this paper · explained in 2 episodes
• Benchmark — 14× in this paper · explained in 2 episodes
• Robustness — 9× in this paper · explained in 5 episodes
• Counterfactual Brier Score — 6× in this paper
• Trace — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Adversarial Robustness — 2× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Chain-of-Thought Prompting — 2× in this paper · explained in 2 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Introspection — 2× in this paper · explained in 2 episodes
• Reasoning Traces — 2× in this paper · explained in 3 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Sample Complexity — 2× in this paper · explained in 15 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Causal Reasoning — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hallucination Detection — 1× in this paper · explained in 2 episodes

Sources

• Learning to Give Checkable Answers with Prover-Verifier Games
• Measuring Progress on Scalable Oversight for Large Language Models
• Training Verifiers to Solve Math Word Problems
• DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
• RFEval: Benchmarking Reasoning Faithfulness under Counterfactual Reasoning Intervention in Large Reasoning Models
• AI safety via debate
• Prover-Verifier Games improve legibility of LLM outputs
• Measuring Faithfulness in Chain-of-Thought Reasoning
• A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior
• Truthfulness Despite Weak Supervision: Evaluating and Training LLMs Using Peer Prediction
• Question Decomposition Improves the Faithfulness of Model-Generated Reasoning
• ElicitationGPT: Text Elicitation Mechanisms via Language Models

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering