3 papers
cs.AI2026
R-C2: Cycle-Consistent Reinforcement Learning Improves Multimodal Reasoning
Zirui Zhang, Haoyu Dong, Kexin Pei +1
Robust perception and reasoning require consistency across sensory modalities. Yet current multimodal models often violate this principle, yielding contradictory predictions for vi…
cs.AI2025
Jupiter: Enhancing LLM Data Analysis Capabilities via Notebook and Inference-Time Value-Guided Search
Shuocheng Li, Yihao Liu, Silin Du +7
Large language models (LLMs) have shown great promise in automating data science workflows, but existing models still struggle with multi-step reasoning and tool use, which limits…
cs.CL2024
MMedAgent: Learning to Use Medical Tools with Multi-modal Agent
Binxu Li, Tiankai Yan, Yuanting Pan +8
Multi-Modal Large Language Models (MLLMs), despite being successful, exhibit limited generality and often fall short when compared to specialized models. Recently, LLM-based agents…