5 citations · 5 across the 4 of their papers we have counts for
7 papers
Scaling Language-Centric Omnimodal Representation Learning
Chenghao Xiao, Hou Pong Chan, Hao Zhang +3
Recent multimodal embedding approaches leveraging multimodal large language models (MLLMs) fine-tuned with contrastive learning (CL) have shown promising results, yet the underlyin…
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…
VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Ruifeng Yuan, Chenghao Xiao, Sicong Leng +9
Reinforcement learning has proven its effectiveness in enhancing the reasoning capabilities of large language models. Recent research efforts have progressively extended this parad…
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…
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Yu Sun, Xingyu Qian, Weiwen Xu +8
Reasoning-based large language models have excelled in mathematics and programming, yet their potential in knowledge-intensive medical question answering remains underexplored and…
Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
Chenghao Xiao, Hou Pong Chan, Hao Zhang +4
While understanding the knowledge boundaries of LLMs is crucial to prevent hallucination, research on the knowledge boundaries of LLMs has predominantly focused on English. In this…