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Preprint Aug 2026

Aligning Human Sense: Calibrated Distributional Reward Learning for Video Generation

Video generation is central to AI-powered content creation. Aligning generated videos with human preferences is a key criterion for evaluating generation quality. Despite significant progress in visual quality, three key challenges remain. First, the reliability of reward signals is constrained by the quality of human...

Naixin Zhai, Weihua Cheng, De-Xu Yu et al. · 0 citations
Preprint Sep 2026

Recommender System as Slow and Fast Thinkers

Experiments on five real-world datasets show that \textsc{DS-Frame} consistently improves representative sequential recommendation backbones, with larger gains on challenging groups and effective accuracy--efficiency trade-offs, highlighting the potential of adaptive inference for more efficient and robust recommendati...

Zichen Yuan, Xiao-Xuan Dong, Linkun Dai et al. · 0 citations
Preprint Aug 2026

Risk-Aware Reranking for Agentic Tool Retrieval

Tool retrieval determines which external tools are exposed to an LLM agent for a user query or task, making retrieval a critical pre-execution safety boundary. Unlike document retrieval, tool retrieval exposes executable actions: a tool that is useful for one task may be unnecessary or risky for another. However, exist...

Qinfei Li, Xiaoxuan Dong, Jin Zhang et al. · 0 citations
#artificial intelligence Preprint Aug 2026

From Uncertainty to Clinical Risk: Severity-Aware Conformal Planning for Interactive Medical Diagnosis

S Severity-Aware Conformal Clinical Planning formulates interactive diagnosis as a risk-sensitive sequential decision problem and achieves more accurate diagnoses with fewer questions across multiple large language models, while improving differential-diagnosis quality and reducing high-risk errors in severe cases.

Yue Zhou, Haisu Zhou, Jin Zhang et al. · 0 citations

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