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Meitang Li

2 accepted papers

2026

VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use

ICLR 2026poster

Reinforcement learning finetuning (RFT) has significantly advanced the reasoning capabilities of large language models (LLMs) by enabling long chains of thought, multi-turn self-correction, and effective tool use. While recent works attempt to extend RFT to vision-language models (VLMs), these effor…

Cited by 0SourcecodeScholar
2025

Cache-of-Thought: Master-Apprentice Framework for Cost-Effective Vision Language Model Reasoning

EMNLP 2025

Vision Language Models (VLMs) have achieved remarkable success in a wide range of vision applications of increasing complexity and scales, yet choosing the right VLM model size involves a trade-off between response quality and cost. While smaller VLMs are cheaper to run, they typically produce respo