9 papers
VCSearch: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning
Shi-Yu Tian, Zhi Zhou, Kun-Yang Yu +4
Large language models (LLMs) have demonstrated impressive performance on reasoning tasks, including mathematical reasoning. However, the current evaluation mostly focuses on carefu…
Vision-Language Model Selection and Reuse for Downstream Adaptation
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li +1
Pre-trained Vision-Language Models (VLMs) are becoming increasingly popular across various visual tasks, and several open-sourced VLM variants have been released. However, selectin…
Enabling Small Models for Zero-Shot Selection and Reuse through Model Label Learning
Jia Zhang, Zhi Zhou, Lan-Zhe Guo +1
Vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot ability in image classification tasks by aligning text and images but suffer inferior performance com…
You Only Submit One Image to Find the Most Suitable Generative Model
Zhi Zhou, Lan-Zhe Guo, Peng-Xiao Song +1
Deep generative models have achieved promising results in image generation, and various generative model hubs, e.g., Hugging Face and Civitai, have been developed that enable model…
Fully Test-time Adaptation for Tabular Data
Zhi Zhou, Kun-Yang Yu, Lan-Zhe Guo +1
Tabular data plays a vital role in various real-world scenarios and finds extensive applications. Although recent deep tabular models have shown remarkable success, they still stru…
Neuro-Symbolic Data Generation for Math Reasoning
Zenan Li, Zhi Zhou, Yuan Yao +5
A critical question about Large Language Models (LLMs) is whether their apparent deficiency in mathematical reasoning is inherent, or merely a result of insufficient exposure to hi…