48 citations · 212 across the 28 of their papers we have counts for
29 papers
Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Senqiao Yang, Chengyao Wang, Yuxin Chen +13
Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodie…
VisionZip: Longer is Better but Not Necessary in Vision Language Models
Senqiao Yang, Yukang Chen, Zhuotao Tian +4
Recent advancements in vision-language models have enhanced performance by increasing the length of visual tokens, making them much longer than text tokens and significantly raisin…
Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models
Longxiang Tang, Zhuotao Tian, Kai Li +5
This study addresses the Domain-Class Incremental Learning problem, a realistic but challenging continual learning scenario where both the domain distribution and target classes va…
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…
Scalable Language Model with Generalized Continual Learning
Bohao Peng, Zhuotao Tian, Shu Liu +2
Continual learning has gained increasing importance as it facilitates the acquisition and refinement of scalable knowledge and skills in language models. However, existing methods…
Unified Language-driven Zero-shot Domain Adaptation
Senqiao Yang, Zhuotao Tian, Li Jiang +1
This paper introduces Unified Language-driven Zero-shot Domain Adaptation (ULDA), a novel task setting that enables a single model to adapt to diverse target domains without explic…