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20242026
most citedEnhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Zero-shot Multivariate Time Series Forecasting Using Tabular Prior Fitted Networks

Mayuka Jayawardhana, Nihal Sharma, Kazem Meidani +3

Tabular foundation models, particularly Prior-data Fitted Networks like TabPFN have emerged as the leading contender in a myriad of tasks ranging from data imputation to label pred…

cs.CV2025★ 1 cited

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Jiuhai Chen, Zhiyang Xu, Xichen Pan +10

Unifying image understanding and generation has gained growing attention in recent research on multimodal models. Although design choices for image understanding have been extensiv…

cs.LG2024

OPTune: Efficient Online Preference Tuning

Lichang Chen, Jiuhai Chen, Chenxi Liu +6

Reinforcement learning with human feedback~(RLHF) is critical for aligning Large Language Models (LLMs) with human preference. Compared to the widely studied offline version of RLH…

cs.CV2024★ 3 cited

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement

Xiyao Wang, Jiuhai Chen, Zhaoyang Wang +8

Large vision-language models (LVLMs) have achieved impressive results in visual question-answering and reasoning tasks through vision instruction tuning on specific datasets. Howev…

cs.LG2024★ 1 cited

ODIN: Disentangled Reward Mitigates Hacking in RLHF

Lichang Chen, Chen Zhu, Davit Soselia +6

In this work, we study the issue of reward hacking on the response length, a challenge emerging in Reinforcement Learning from Human Feedback (RLHF) on LLMs. A well-formatted, verb…