1 citations · 1 across the 5 of their papers we have counts for
9 papers
FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting
Zefeng He, Xiaoye Qu, Yafu Li +3
While Large Vision-Language Models (LVLMs) have achieved substantial progress in video understanding, their application to long video reasoning is hindered by uniform frame samplin…
Towards an AI Musician: Synthesizing Sheet Music Problems for Musical Reasoning
Zhilin Wang, Zhe Yang, Yun Luo +8
Enhancing the ability of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) to interpret sheet music is a crucial step toward building AI musicians. However,…
Advancing Multimodal Reasoning: From Optimized Cold Start to Staged Reinforcement Learning
Shuang Chen, Yue Guo, Zhaochen Su +7
Inspired by the remarkable reasoning capabilities of Deepseek-R1 in complex textual tasks, many works attempt to incentivize similar capabilities in Multimodal Large Language Model…
SEE: Continual Fine-tuning with Sequential Ensemble of Experts
Zhilin Wang, Yafu Li, Xiaoye Qu +1
Continual fine-tuning of large language models (LLMs) suffers from catastrophic forgetting. Rehearsal-based methods mitigate this problem by retaining a small set of old data. Neve…
A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond
Xiaoye Qu, Yafu Li, Zhao-Chen Su +15
Recent Large Reasoning Models (LRMs), such as DeepSeek-R1 and OpenAI o1, have demonstrated strong performance gains by scaling up the length of Chain-of-Thought (CoT) reasoning dur…
Multi-LLM Collaborative Search for Complex Problem Solving
Sen Yang, Yafu Li, Wai Lam +1
Large language models (LLMs) often struggle with complex reasoning tasks due to their limitations in addressing the vast reasoning space and inherent ambiguities of natural languag…