arXiv AI
Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators
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Not All Skills Help: Measuring and Repairing Agent Knowledge
arXiv:2606. 15390v1 Announce Type: cross Abstract: LLM agents can improve without weight updates by accumulating natural-language skills from experience, but current systems entrust every decision about which skills to keep and how to apply them to LLM judgment alone.
arXiv AI
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Human Interventions as Labels: Localizing, Steering, and (Sometimes) Editing the Computations Behind LLM Agent Failures
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arXiv AI
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It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories
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arXiv AI
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Do LLMs Know What to Ask and When? Evaluating Multi-Turn Information Seeking
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arXiv AI
Sep 10
CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows
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arXiv AI
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Masked Distillation: Internalizing the Chain-of-Thought in Language Models
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