Training on Synthetic Data

• Haoxin Li and Boyang Li. Enhancing Vision-Language Compositional Understanding with Multimodal Synthetic Data. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2025. [Code]
• Tong Zhang, Mengao Zhang, Wei Yan Low, X. Jessie Yang, and Boyang Li. Conversational Explanations: Discussing Explainable AI with Non-AI Experts. The ACM Conference on Intelligent User Interfaces (IUI). 2025
• Xu Guo, Zilin Du, Boyang Li, and Chunyan Miao. Generating Synthetic Datasets for Few-shot Prompt Tuning. The First Conference on Language Modeling (COLM). 2024.
• Zilin Du, Yunxin Li, Xu Guo, Yidan Sun, and Boyang Li. Training Multimedia Event Extraction With Generated Images and Captions. The ACM International Conference on Multimedia (ACM MM). 2023. [Code]
• Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, and Lidong Bing. Is GPT-3 a Good Data Annotator? The Annual Conference of the Association for Computational Linguistics (ACL). 2023.

Pruning Training Data

• Jaewoo Lee, Boyang Li, and Sung Ju Hwang. Concept-skill Transferability-based Data Selection for Large Vision-Language Models. The Conference on Empirical Methods in Natural Language Processing (EMNLP). 2024. [Code]
• Devaansh Gupta and Boyang Li. Training Data Recipe to Accelerate A* Search with Large Language Models. Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP Findings). 2024. [Code]

Understanding Data

• Anthony Tiong, Junqi Zhao, Boyang Li, Junnan Li, Steven Hoi, and Caiming Xiong. What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases. The 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). 2024. [Dataset]
• Yuanyuan Chen, Boyang Li, Han Yu, Pengcheng Wu, and Chunyan Miao. HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks. The AAAI Conference on Artificial Intelligence (AAAI). 2021. [Code]