GRACE is proposed, a Graph-based Rationalized CoT Compression framework that transforms long CoTs into reasoning graphs to enable efficient CoT compression, where reasoning steps are represented as nodes and semantic dependencies as edges.
Yizhi Wang, Li-Nan Yue, Deng-Bao Wang et al.· Proceedings of the 32nd ACM...· 0 citations
SafeIMG is introduced, a safety-oriented benchmark spanning 12 public- and individual-safety scenarios generated using GPT Image 2.0 that provides human annotations that localise suspicious regions and explain local artefacts and higher-level commonsense or physical inconsistencies.
Yizhi Wang, Yichen Xiao, Linan Yue et al.· 0 citations
Recent advances in multimodal large reasoning models (MLRMs) have demonstrated impressive capabilities on complex multimodal tasks, yet their reliance on long Chain-of-Thoughts (CoTs) often leads to redundant reasoning and high computational cost. Existing chain-based distillation and refinement approaches alleviate re...
Yizhi Wang, Linan Yue, Deng-Bao Wang et al.· Proceedings of the 32nd ACM...· 0 citations
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