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Si-Yuan Li

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#machine learning Review Sep 2026

Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework

Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step error amplification, prompt brittleness, and failures to revise incorrect commitments are difficult to explain by missing knowledge or expressive capacity alone. This su...

Jia-Zhang Cai, Tao Wang, Rui-Dong Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Anchoring What Matters: A Dual-Level Learning Framework for Visually-Grounded Multimodal Reasoning

Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capabilities of large vision-language models (LVLMs). However, standard on-policy RLVR algorithms face a critical optimization bottleneck in preserving and reinforcing visually grounded reasoning behaviors: valuable visually-...

Xin-Xin Song, Si-Yuan Li, Tingxiong Xiao et al. · 0 citations
#artificial intelligence Preprint Sep 2026

CARE: Contrastive Anchor-based Rubric Evolution for Large Language Model Post-Training

CARE is proposed, which grounds every rubric evolution step in a high-quality anchor response generated by a frontier model conditioned on the prompt and its rubrics, enabling two complementary mechanisms: an Adaptive branch that reactively repairs reward misspecification; and a Chase branch that proactively converts f...

Si-Yuan Li, Xin-Xin Song, Rui-Nian Chen et al. · 0 citations

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