Publications

See my Google Scholar for the most up-to-date list of papers.

2026

  1. arXiv
    abstain.png
    Are LLM Decisions Faithful to Verbal Confidence?
    Jiawei Wang , Yanfei Zhou, Siddartha Devic, and Deqing Fu
    2026
    📄 Paper
  2. ICLR
    zebra-cot.png
    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 International Conference on Learning Representations (ICLR), 2026
    *Equal Contribution
    📄 Paper Hugging Face Dataset
  3. ICLR
    fone.png
    FoNE: Precise Single-Token Number Embeddings via Fourier Features
    Tianyi Zhou, Deqing Fu, Mahdi Soltanolkotabi, Robin Jia, and Vatsal Sharan
    In International Conference on Learning Representations (ICLR), 2026
    📄 Paper Website

2025

  1. arXiv
    graph.png
    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
    resa.png
    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
  3. arXiv
    saegull.png
    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
  4. NeurIPS
    visuallens.png
    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
  5. ICLR
    tldr.png
    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
  6. ICLR
    sensitivity.png
    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
  7. ICLR
    dellma.png
    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 GitHub Code Website
  8. NAACL
    dreamsync.png
    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
    transformer-icl.png
    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 GitHub Code
  2. NeurIPS
    fourier.png
    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.png
    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.png
    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 GitHub Code