7 citations · 14 across the 5 of their papers we have counts for
5 papers
GeoPQA: Bridging the Visual Perception Gap in MLLMs for Geometric Reasoning
Guizhen Chen, Weiwen Xu, Hao Zhang +4
Recent advancements in reinforcement learning (RL) have enhanced the reasoning abilities of large language models (LLMs), yet the impact on multimodal LLMs (MLLMs) is limited. Part…
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
LASA Team, Weiwen Xu, Hou Pong Chan +16
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements, largely due to their large-scale datasets and advanced t…
Pruning General Large Language Models into Customized Expert Models
Yirao Zhao, Guizhen Chen, Kenji Kawaguchi +2
Large language models (LLMs) have revolutionized natural language processing, yet their substantial model sizes often require substantial computational resources. To preserve compu…
Contrastive Chain-of-Thought Prompting
Yew Ken Chia, Guizhen Chen, Luu Anh Tuan +2
Despite the success of chain of thought in enhancing language model reasoning, the underlying process remains less well understood. Although logically sound reasoning appears inher…
Zero-Shot Text Classification via Self-Supervised Tuning
Chaoqun Liu, Wenxuan Zhang, Guizhen Chen +4
Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to the choices of templates, or rely on large-scal…