Grad Detect uses internal gradient patterns from one inference pass to predict LLM hallucinations and abstention, outperforming confidence and sampling baselines on Q&A benchmarks with most signal in the final five layers.
Rcot: Detecting and rectifying factual inconsistency in reasoning by reversing chain-of-thought
4 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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A pipeline produces 54,000 execution-trace-verified bi-directional Chain-of-Thought rationales for code, and fine-tuning on them yields gains up to 26.6 points on LiveCodeBench-Exec and similar benchmarks.
Inclusion-of-Thoughts progressively filters out implausible MCQ distractors so LLMs focus on remaining options and report more stable chain-of-thought answers.
citing papers explorer
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Grad Detect: Gradient-Based Hallucination Detection in LLMs
Grad Detect uses internal gradient patterns from one inference pass to predict LLM hallucinations and abstention, outperforming confidence and sampling baselines on Q&A benchmarks with most signal in the final five layers.
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Generating Verifiable Chain of Thoughts from Exection-Traces
A pipeline produces 54,000 execution-trace-verified bi-directional Chain-of-Thought rationales for code, and fine-tuning on them yields gains up to 26.6 points on LiveCodeBench-Exec and similar benchmarks.
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Inclusion-of-Thoughts: Mitigating Preference Instability via Purifying the Decision Space
Inclusion-of-Thoughts progressively filters out implausible MCQ distractors so LLMs focus on remaining options and report more stable chain-of-thought answers.
- A Taxonomy of Single-Turn Textual Prompt Patterns