5 citations · 5 across the 3 of their papers we have counts for
10 papers · 1 filter
Reflect to Inform: Boosting Multimodal Reasoning via Information-Gain-Driven Verification
Shuai Lv, Chang Liu, Feng Tang +5
Multimodal Large Language Models (MLLMs) achieve strong multimodal reasoning performance, yet we identify a recurring failure mode in long-form generation: as outputs grow longer,…
MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning
Weikang Shi, Aldrich Yu, Rongyao Fang +11
While Large Language Models (LLMs) have excelled in textual reasoning, they struggle with mathematical domains like geometry that intrinsically rely on visual aids. Existing approa…
Chimera: Improving Generalist Model with Domain-Specific Experts
Tianshuo Peng, Mingsheng Li, Jiakang Yuan +11
Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks.…
MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning
Xinyan Chen, Renrui Zhang, Dongzhi Jiang +4
Chain-of-Thought (CoT) has widely enhanced mathematical reasoning in Large Language Models (LLMs), but it still remains challenging for extending it to multimodal domains. Existing…
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Ke Wang, Junting Pan, Linda Wei +8
Natural language image-caption datasets, widely used for training Large Multimodal Models, mainly focus on natural scenarios and overlook the intricate details of mathematical figu…
Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding
Han Xiao, Yina Xie, Guanxin Tan +12
Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration…