DEONTICBENCH is a new benchmark of 6,232 deontic reasoning tasks from U.S. legal domains where frontier LLMs reach only ~45% accuracy and symbolic Prolog assistance plus RL training still fail to solve tasks reliably.
Chain-of- thought prompting obscures hallucination cues in large language models: An empirical evaluation
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Across 9 VLMs and 9,000 pairs, 72.9% of cases show Visual Sycophancy (split beliefs: vision preserved, wrong answer decoded), zero show robust refusal, and scale worsens the pattern while cutting language shortcuts.
ARS shapes reasoning trace representations by clustering states that produce consistent answers and separating those that produce inconsistent ones via latent perturbations, improving plug-and-play hallucination detection without human annotations.
ConsisGuard is a consistency-aware framework that applies Policy-to-Decision Trajectory Distillation and Functional Coupling Alignment to improve policy execution consistency in reasoning-based LLM guardrails on harmfulness detection tasks.
A 16-factor structured prompt framework strengthens CoT reasoning in LLMs for security analysis, yielding up to 40% reasoning gains in smaller models and stable accuracy improvements validated by human raters with Cohen's k > 0.80.
The paper unifies perspectives on Long CoT in reasoning LLMs by introducing a taxonomy, detailing characteristics of deep reasoning and reflection, and discussing emergence phenomena and future directions.
citing papers explorer
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DeonticBench: A Benchmark for Reasoning over Rules
DEONTICBENCH is a new benchmark of 6,232 deontic reasoning tasks from U.S. legal domains where frontier LLMs reach only ~45% accuracy and symbolic Prolog assistance plus RL training still fail to solve tasks reliably.
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To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs
Across 9 VLMs and 9,000 pairs, 72.9% of cases show Visual Sycophancy (split beliefs: vision preserved, wrong answer decoded), zero show robust refusal, and scale worsens the pattern while cutting language shortcuts.
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Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping
ARS shapes reasoning trace representations by clustering states that produce consistent answers and separating those that produce inconsistent ones via latent perturbations, improving plug-and-play hallucination detection without human annotations.
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ConsisGuard: Aligning Safety Deliberation with Policy Enforcement in LLM Guardrails
ConsisGuard is a consistency-aware framework that applies Policy-to-Decision Trajectory Distillation and Functional Coupling Alignment to improve policy execution consistency in reasoning-based LLM guardrails on harmfulness detection tasks.
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Strengthening Human-Centric Chain-of-Thought Reasoning Integrity in LLMs via a Structured Prompt Framework
A 16-factor structured prompt framework strengthens CoT reasoning in LLMs for security analysis, yielding up to 40% reasoning gains in smaller models and stable accuracy improvements validated by human raters with Cohen's k > 0.80.
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Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models
The paper unifies perspectives on Long CoT in reasoning LLMs by introducing a taxonomy, detailing characteristics of deep reasoning and reflection, and discussing emergence phenomena and future directions.