5 papers
AgriChain Visually Grounded Expert Verified Reasoning for Interpretable Agricultural Vision Language Models
Hazza Mahmood, Yongqiang Yu, Rao Anwer
Accurate and interpretable plant disease diagnosis remains a major challenge for vision-language models (VLMs) in real-world agriculture. We introduce AgriChain, a dataset of appro…
MediX-R1: Open Ended Medical Reinforcement Learning
Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Omair Mohamed +5
We introduce MediX-R1, an open-ended Reinforcement Learning (RL) framework for medical multimodal large language models (MLLMs) that enables clinically grounded, free-form answers…
Thinking Beyond Labels: Vocabulary-Free Fine-Grained Recognition using Reasoning-Augmented LMMs
Dmitry Demidov, Zaigham Zaheer, Zongyan Han +2
Vocabulary-free fine-grained image recognition aims to distinguish visually similar categories within a meta-class without a fixed, human-defined label set. Existing solutions for…
MATRIX: Multimodal Agent Tuning for Robust Tool-Use Reasoning
Tajamul Ashraf, Umair Nawaz, Abdelrahman M. Shaker +4
Vision language models (VLMs) are increasingly deployed as controllers with access to external tools for complex reasoning and decision-making, yet their effectiveness remains limi…
MIRA: A Novel Framework for Fusing Modalities in Medical RAG
Jinhong Wang, Tajamul Ashraf, Zongyan Han +2
Multimodal Large Language Models (MLLMs) have significantly advanced AI-assisted medical diagnosis, but they often generate factually inconsistent responses that deviate from estab…