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cs.CL2026
Quantifying the Gap between Understanding and Generation within Unified Multimodal Models
Chenlong Wang, Yuhang Chen, Zhihan Hu +4
Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whether these two capabilities are gen…
cs.CL2025
Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency
Chenlong Wang, Yuanning Feng, Dongping Chen +3
Recent advances in large reasoning models have enabled complex, step-by-step reasoning but often introduce significant overthinking, resulting in verbose and redundant outputs that…
cs.CL2025
CODESYNC: Synchronizing Large Language Models with Dynamic Code Evolution at Scale
Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng +6
Large Language Models (LLMs) have exhibited exceptional performance in software engineering yet face challenges in adapting to continually evolving code knowledge, particularly reg…