7 papers
On the Perception Bottleneck of VLMs for Chart Understanding
Junteng Liu, Weihao Zeng, Xiwen Zhang +3
Chart understanding requires models to effectively analyze and reason about numerical data, textual elements, and complex visual components. Our observations reveal that the percep…
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild
Weihao Zeng, Yuzhen Huang, Qian Liu +4
DeepSeek-R1 has shown that long chain-of-thought (CoT) reasoning can naturally emerge through a simple reinforcement learning (RL) framework with rule-based rewards, where the trai…
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Weihao Zeng, Yuzhen Huang, Lulu Zhao +3
In the absence of extensive human-annotated data for complex reasoning tasks, self-improvement -- where models are trained on their own outputs -- has emerged as a primary method f…
CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery
Xiaoshuai Song, Muxi Diao, Guanting Dong +13
Large language models (LLMs) have demonstrated significant potential in advancing various fields of research and society. However, the current community of LLMs overly focuses on b…
AgentRefine: Enhancing Agent Generalization through Refinement Tuning
Dayuan Fu, Keqing He, Yejie Wang +7
Large Language Model (LLM) based agents have proved their ability to perform complex tasks like humans. However, there is still a large gap between open-sourced LLMs and commercial…
CareBot: A Pioneering Full-Process Open-Source Medical Language Model
Lulu Zhao, Weihao Zeng, Xiaofeng Shi +1
Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific…