127 citations · 152 across the 21 of their papers we have counts for
5 papers · 1 filter
Surrogate Signals from Format and Length: Reinforcement Learning for Solving Mathematical Problems without Ground Truth Answers
Rihui Xin, Han Liu, Zecheng Wang +4
Large Language Models (LLMs) have achieved remarkable success in natural language processing tasks, with Reinforcement Learning (RL) playing a key role in adapting them to specific…
Efficient Motion-Aware Video MLLM
Zijia Zhao, Yuqi Huo, Tongtian Yue +5
Most current video MLLMs rely on uniform frame sampling and image-level encoders, resulting in inefficient data processing and limited motion awareness. To address these challenges…
Baichuan-M1: Pushing the Medical Capability of Large Language Models
Bingning Wang, Haizhou Zhao, Huozhi Zhou +39
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like…
Virgo: A Preliminary Exploration on Reproducing o1-like MLLM
Yifan Du, Zikang Liu, Yifan Li +7
Recently, slow-thinking reasoning systems, built upon large language models (LLMs), have garnered widespread attention by scaling the thinking time during inference. There is also…
LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation
Zican Dong, Junyi Li, Jinhao Jiang +4
Large language models (LLMs) have gained extended context windows through scaling positional encodings and lightweight continual pre-training. However, this often leads to degraded…