3 papers
cs.CV2025
VLM-FO1: Bridging the Gap Between High-Level Reasoning and Fine-Grained Perception in VLMs
Peng Liu, Haozhan Shen, Chunxin Fang +3
Vision-Language Models (VLMs) excel at high-level scene understanding but falter on fine-grained perception tasks requiring precise localization. This failure stems from a fundamen…
cs.CL2025
Unifying Language Agent Algorithms with Graph-based Orchestration Engine for Reproducible Agent Research
Qianqian Zhang, Jiajia Liao, Heting Ying +9
Language agents powered by large language models (LLMs) have demonstrated remarkable capabilities in understanding, reasoning, and executing complex tasks. However, developing robu…
cs.CV2025
VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
Haozhan Shen, Peng Liu, Jingcheng Li +9
Recently DeepSeek R1 has shown that reinforcement learning (RL) can substantially improve the reasoning capabilities of Large Language Models (LLMs) through a simple yet effective…