5 papers
Probability-Consistent Preference Optimization for Enhanced LLM Reasoning
Yunqiao Yang, Houxing Ren, Zimu Lu +6
Recent advances in preference optimization have demonstrated significant potential for improving mathematical reasoning capabilities in large language models (LLMs). While current…
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Ke Wang, Junting Pan, Linda Wei +8
Natural language image-caption datasets, widely used for training Large Multimodal Models, mainly focus on natural scenarios and overlook the intricate details of mathematical figu…
Hiding Images in Diffusion Models by Editing Learned Score Functions
Haoyu Chen, Yunqiao Yang, Nan Zhong +1
Hiding data using neural networks (i.e., neural steganography) has achieved remarkable success across both discriminative classifiers and generative adversarial networks. However,…
Learning Where to Edit Vision Transformers
Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen +2
Model editing aims to data-efficiently correct predictive errors of large pre-trained models while ensuring generalization to neighboring failures and locality to minimize unintend…
Concept-wise Fine-tuning Matters in Preventing Negative Transfer
Yunqiao Yang, Long-Kai Huang, Ying Wei
A multitude of prevalent pre-trained models mark a major milestone in the development of artificial intelligence, while fine-tuning has been a common practice that enables pretrain…