2 citations · 2 across the 4 of their papers we have counts for
4 papers
A benchmark multimodal oro-dental dataset for large vision-language models
Haoxin Lv, Ijazul Haq, Jin Du +7
The advancement of artificial intelligence in oral healthcare relies on the availability of large-scale multimodal datasets that capture the complexity of clinical practice. In thi…
Learning Contrastive Multimodal Fusion with Improved Modality Dropout for Disease Detection and Prediction
Yi Gu, Kuniaki Saito, Jiaxin Ma
As medical diagnoses increasingly leverage multimodal data, machine learning models are expected to effectively fuse heterogeneous information while remaining robust to missing mod…
Can Compact Language Models Search Like Agents? Distillation-Guided Policy Optimization for Preserving Agentic RAG Capabilities
Rikuto Kotoge, Mai Nishimura, Jiaxin Ma
Reinforcement Learning has emerged as a dominant post-training approach to elicit agentic RAG behaviors such as search and planning from language models. Despite its success with l…
Adaptive Distillation for Decentralized Learning from Heterogeneous Clients
Jiaxin Ma, Ryo Yonetani, Zahid Iqbal
This paper addresses the problem of decentralized learning to achieve a high-performance global model by asking a group of clients to share local models pre-trained with their own…