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Optimizing Length Compression in Large Reasoning Models
Zhengxiang Cheng, Dongping Chen, Mingyang Fu +1
Large Reasoning Models (LRMs) have achieved remarkable success, yet they often suffer from producing unnecessary and verbose reasoning chains. We identify a core aspect of this iss…
Reinforced Visual Perception with Tools
Zetong Zhou, Dongping Chen, Zixian Ma +6
Visual reasoning, a cornerstone of human intelligence, encompasses complex perceptual and logical processes essential for solving diverse visual problems. While advances in compute…
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…
REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
Peter Sushko, Ayana Bharadwaj, Zhi Yang Lim +6
Existing image editing models struggle to meet real-world demands. Despite excelling in academic benchmarks, they have yet to be widely adopted for real user needs. Datasets that p…