4 papers · 1 filter
First SFT, Second RL, Third UPT: Continual Improving Multi-Modal LLM Reasoning via Unsupervised Post-Training
Lai Wei, Yuting Li, Chen Wang +4
Improving Multi-modal Large Language Models (MLLMs) in the post-training stage typically relies on supervised fine-tuning (SFT) or reinforcement learning (RL), which require expens…
Advancing Multimodal Reasoning via Reinforcement Learning with Cold Start
Lai Wei, Yuting Li, Kaipeng Zheng +5
Recent advancements in large language models (LLMs) have demonstrated impressive chain-of-thought reasoning capabilities, with reinforcement learning (RL) playing a crucial role in…
Benchmarking LLMs for Political Science: A United Nations Perspective
Yueqing Liang, Liangwei Yang, Chen Wang +6
Large Language Models (LLMs) have achieved significant advances in natural language processing, yet their potential for high-stake political decision-making remains largely unexplo…
A longitudinal sentiment analysis of Sinophobia during COVID-19 using large language models
Chen Wang, Rohitash Chandra
The COVID-19 pandemic has exacerbated xenophobia, particularly Sinophobia, leading to widespread discrimination against individuals of Chinese descent. Large language models (LLMs)…