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cs.SE2026
TaoD2C-Bench: Benchmarking MLLMs for Industrial UI Code Generation Beyond Visual Fidelity
Chengwei Shi, Yunnong Chen, Tingting Zhou +5
A key challenge for multimodal large language models (MLLMs) is moving beyond visual recognition to constraint-aware cross-modal reasoning. This involves combining visual cues with…
cs.SE2026
On Reasoning-Centric LLM-based Automated Theorem Proving
Yican Sun, Chengwei Shi, Hangzhou Lyu +1
Automated theorem proving is fundamental to formal methods, and the recent trend is to integrate large language models (LLMs) and proof assistants to form effective proof agents. W…