9 papers
On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
Yongliang Wu, Yizhou Zhou, Zhou Ziheng +7
In this work, we present a simple yet theoretically motivated improvement to Supervised Fine-Tuning (SFT) for the Large Language Model (LLM), addressing its limited generalization…
DeQA-Doc: Adapting DeQA-Score to Document Image Quality Assessment
Junjie Gao, Runze Liu, Yingzhe Peng +4
Document quality assessment is critical for a wide range of applications including document digitization, OCR, and archival. However, existing approaches often struggle to provide…
L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training
Li Li, Yingzhe Peng, Xu Yang +4
We propose a novel embedding-based captioning metric termed as L-CLIPScore that can be used for efficiently evaluating caption quality and training captioning model. L-CLIPScore is…
Mimic In-Context Learning for Multimodal Tasks
Yuchu Jiang, Jiale Fu, Chenduo Hao +4
Recently, In-context Learning (ICL) has become a significant inference paradigm in Large Multimodal Models (LMMs), utilizing a few in-context demonstrations (ICDs) to prompt LMMs f…
Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
Yingzhe Peng, Xiaoting Qin, Zhiyang Zhang +6
The rise of large language models (LLMs) has revolutionized user interactions with knowledge-based systems, enabling chatbots to synthesize vast amounts of information and assist w…
LIVE: Learnable In-Context Vector for Visual Question Answering
Yingzhe Peng, Chenduo Hao, Xu Yang +3
As language models continue to scale, Large Language Models (LLMs) have exhibited emerging capabilities in In-Context Learning (ICL), enabling them to solve language tasks by prefi…