Publications

2025

1. arXiv

   

   When Do Transformers Learn Heuristics for Graph Connectivity?

   Qilin Ye^*, Deqing Fu^*, Robin Jia, and Vatsal Sharan

   In arXiv, 2025

   *Equal Contribution

   📄 Paper
2. arXiv

   

   Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning

   Ang Li^*, Charles Wang^*, Deqing Fu^*, Kaiyu Yue^*, Zikui Cai^*, Wang Bill Zhu^*, Ollie Liu^*, Peng Guo^*, Willie Neiswanger, Furong Huang, Tom Goldstein, and Micah Goldblum

   In arXiv, 2025

   *Equal Contribution

   📄 Paper Dataset
3. arXiv

   

   Resa: Transparent Reasoning Models via SAEs

   Shangshang Wang, Julian Asilis, Ömer Faruk Akgül, Enes Burak Bilgin, Ollie Liu, Deqing Fu, and Willie Neiswanger

   In arXiv, 2025

   📄 Paper
4. arXiv

   

   Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models

   Woody Haosheng Gan^*, Deqing Fu^*, Julian Asilis^*, Ollie Liu^*, Dani Yogatama, Vatsal Sharan, Robin Jia, and Willie Neiswanger

   In arXiv, 2025

   *Equal Contribution

   📄 Paper Blog
5. arXiv

   

   FoNE: Precise Single-Token Number Embeddings via Fourier Features

   Tianyi Zhou, Deqing Fu, Mahdi Soltanolkotabi, Robin Jia, and Vatsal Sharan

   In arXiv, 2025

   📄 Paper Website
6. NeurIPS

   

   VisualLens: Personalization through Visual History

   Wang Bill Zhu, Deqing Fu , Kai Sun, Yi Lu, Zhaojiang Lin, Seungwhan Moon, Kanika Narang, Mustafa Canim , Yue Liu, Anuj Kumar , and Xin Luna Dong

   In Conference on Neural Information Processing Systems (NeurIPS), 2025

   📄 Paper
7. ICLR

   

   TLDR: Token-Level Detective Reward Model for Large Vision Language Models

   Deqing Fu, Tong Xiao , Rui Wang , Wang Zhu, Pengchuan Zhang, Guan Pang, Robin Jia , and Lawrence Chen

   In International Conference on Learning Representations (ICLR), 2025

   📄 Paper
8. ICLR

   

   Transformers Learn Low Sensitivity Functions: Investigations and Implications

   Bhavya Vasudeva^*, Deqing Fu^*, Tianyi Zhou, Elliot Kau , You-Qi Huang, and Vatsal Sharan

   In International Conference on Learning Representations (ICLR), 2025

   *Equal Contribution

   📄 Paper
9. ICLR

   

   DeLLMa: Decision Making Under Uncertainty with Large Language Models

   Ollie Liu^*, Deqing Fu^*, Dani Yogatama, and Willie Neiswanger

   In International Conference on Learning Representations (ICLR), 2025

   Spotlight (Top 5.1%), *Equal Contribution

   📄 Paper Code Website
10. NAACL

    

    DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback

    Jiao Sun^*, Deqing Fu^*, Yushi Hu^* , Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd Steenkiste, Ranjay Krishna, and Cyrus Rashtchian

    In Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025

    *Equal Contribution

    📄 Paper

2024

1. NeurIPS

   

   Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression

   Deqing Fu , Tian-Qi Chen, Robin Jia, and Vatsal Sharan

   In Conference on Neural Information Processing Systems (NeurIPS), 2024

   SoCalNLP Symposium 2023 Best Paper Award

   📄 Paper Code
2. NeurIPS

   

   Pre-trained Large Language Models Use Fourier Features to Compute Addition

   Tianyi Zhou, Deqing Fu, Vatsal Sharan, and Robin Jia

   In Conference on Neural Information Processing Systems (NeurIPS), 2024

   📄 Paper
3. COLM

   

   IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations

   Deqing Fu^*, Ruohao Guo^*, Ghazal Khalighinejad^*, Ollie Liu^*, Bhuwan Dhingra, Dani Yogatama, Robin Jia, and Willie Neiswanger

   In Conference on Language Modeling (COLM), 2024

   *Equal Contribution

   📄 Paper Website

2023

1. EMNLP

   

   SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples

   Deqing Fu, Ameya Godbole, and Robin Jia

   In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023

   📄 Paper Code