39 citations · 48 across the 5 of their papers we have counts for
6 papers
VideoZoomer: Reinforcement-Learned Temporal Focusing for Long Video Reasoning
Yang Ding, Yizhen Zhang, Xin Lai +2
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in vision-language tasks yet remain limited in long video understanding due to the limited context window…
VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
Senqiao Yang, Junyi Li, Xin Lai +3
Recent advancements in vision-language models (VLMs) have improved performance by increasing the number of visual tokens, which are often significantly longer than text tokens. How…
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Xin Lai, Zhuotao Tian, Yukang Chen +3
Mathematical reasoning presents a significant challenge for Large Language Models (LLMs) due to the extensive and precise chain of reasoning required for accuracy. Ensuring the cor…
LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model
Senqiao Yang, Tianyuan Qu, Xin Lai +4
While LISA effectively bridges the gap between segmentation and large language models to enable reasoning segmentation, it poses certain limitations: unable to distinguish differen…
Mask-Attention-Free Transformer for 3D Instance Segmentation
Xin Lai, Yuhui Yuan, Ruihang Chu +3
Recently, transformer-based methods have dominated 3D instance segmentation, where mask attention is commonly involved. Specifically, object queries are guided by the initial insta…
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Yukang Chen, Shengju Qian, Haotian Tang +4
We present LongLoRA, an efficient fine-tuning approach that extends the context sizes of pre-trained large language models (LLMs), with limited computation cost. Typically, trainin…