Human Feedback and Eval Paper Explorer

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• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

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• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

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• Unlike previous Process Reward Models (PRMs) that rely on static partitioning and human labeling, EDU-PRM automatically anchors step boundaries at tokens with high predictive entropy, effectively capturing intrinsic logical transitions and…
• On the ProcessBench benchmark, EDU-PRM outperforms strong public PRM baselines, such as Math-Shepherd PRM and Omega PRM, and EDU-PRM achieves comparable results with SOTA models while only using 1.5% training data.

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• The LLM-enhanced CLIP delivers consistent improvements across a wide range of downstream tasks, including linear-probe classification, zero-shot image-text retrieval with both short and long captions (in English and other languages),…

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• We then define the frontier cost-of-pass: the minimum cost-of-pass achievable across available models or the human-expert(s), using the approx.

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• Across extensive evaluations, ISM outperforms causal baselines not only on multi-turn dialogue, but also on context-intensive tasks like mathematical reasoning.

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• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

Match reason: Keyword overlap 1/2 across title and protocol fields.

• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

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• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

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• Large language models (LLMs) exhibit strong capabilities as decision-making agents by interleaving reasoning and actions, as seen in ReAct-style frameworks.
• We propose Structured Agent Distillation, a framework that compresses large LLM-based agents into smaller student models while preserving both reasoning fidelity and action consistency.

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• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.