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Wenao Ma

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#artificial intelligence Preprint Sep 2026

Noisy Test-Time Reinforcement Learning for Code LLMs

Large language models (LLMs) have demonstrated remarkable performance across various code-related tasks. However, unlike carefully curated datasets that are typically high-quality and error-free, real-world user instructions are often vague and error-prone, posing significant challenges to the robustness of code LLMs....

Xi-Kai Yang, Hieu Trung Nguyen, Dun-Yuan Xu et al. · 0 citations
Preprint Aug 2026

Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement

FISA is proposed, a framework for MLLM self-improvement that constructs augmented images from the model's own failure cases that generates visually challenging yet answer-preserving image complications, verifies their utility through self-examination, and applies dual fidelity filtering to avoid semantic distortion.

Chun-Yang Jiang, Pingping Zhang, Yuzhi Zhao et al. · 0 citations

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