most citedInfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning

2 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2026

From Parameters to Behaviors: A Survey of Model Fusion for Large Language Models

Shuo Cai, Yanggan Gu, Zihao Wang +8

Model fusion integrates the capabilities from source models into a single target model. As of June 2026, Hugging Face hosts more than 2M models. This growing pool provides a rich b…

cs.AI2026

Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning

Zhitian Hou, Yuhang Liu, Pengkai Wang +8

Applying a valid medication-safety rule when its patient-specific conditions are not met can produce an incorrect decision. Existing medical evaluations largely use isolated and fi…

cs.CL2026

Beyond Captions: Context-Grounded Reconstruction for Biomedical Multimodal Continued Pretraining

Guanghao Zhu, Zeyu Liu, Zhitian Hou +10

Biomedical figures are explained not by captions alone but by body-text passages that discuss them. Yet current multimodal corpora typically reduce figures to isolated image-captio…

cs.AI2025

InfiMed-Foundation: Pioneering Advanced Multimodal Medical Models with Compute-Efficient Pre-Training and Multi-Stage Fine-Tuning

Guanghao Zhu, Zhitian Hou, Zeyu Liu +3

Multimodal large language models (MLLMs) have shown remarkable potential in various domains, yet their application in the medical field is hindered by several challenges. General-p…

cs.AI2025

Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models

Zeyu Liu, Yuhang Liu, Guanghao Zhu +9

Recent advancements in large language models (LLMs) have demonstrated substantial progress in reasoning capabilities, such as DeepSeek-R1, which leverages rule-based reinforcement…

cs.CL2025★ 2 cited

InfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning

Congkai Xie, Shuo Cai, Wenjun Wang +17

Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have made significant advancements in reasoning capabilities. However, they still face challenges such as…