Papers
2024
Pre-trained Large Language Models Use Fourier Features to Compute Addition [paper]
Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia
Arxiv, 2024
IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations [paper, website]
Deqing Fu*, Ghazal Khalighinejad*, Ollie Liu*, Bhuwan Dhingra, Dani Yogatama, Robin Jia, Willie Neiswanger
Arxiv, 2024
*Equal Contribution. Co-first authors ordered alphabetically.
Simplicity Bias of Transformers to Learn Low Sensitivity Functions [paper]
Bhavya Vasudeva*, Deqing Fu*, Tianyi Zhou, Elliot Kau, You-Qi Huang, Vatsal Sharan
Arxiv, 2024
*Equal Contribution.
DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models [paper, codes, website]
Ollie Liu*, Deqing Fu*, Dani Yogatama, Willie Neiswanger
Arxiv, 2024
*Equal Contribution.
2023
Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models [paper, codes]
Deqing Fu, Tian-Qi Chen, Robin Jia, Vatsal Sharan
Arxiv, 2023
SoCalNLP Symposium 2023 Best Paper Award.
DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback [paper]
Jiao Sun*, Deqing Fu*, Yushi Hu*, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, Cyrus Rashtchian
Arxiv, 2023
*Equal Contribution. Work done while at Google.
SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples [paper, codes]
Deqing Fu, Ameya Godbole, Robin Jia.
Empirical Methods in Natural Lanaguge Processing (EMNLP), 2023
2022 and Earlier
Topological Regularization for Dense Prediction [paper]
Deqing Fu, Bradley Nelson.
International Conference on Machine Learning and Applications (ICML-A), 2022 (Oral Presentation)
Harnessing the Conditioning Sensorium for Improved Image Translation [paper]
Cooper Nederhood, Nicholas Kolkin, Deqing Fu, Jason Salavon.
International Conference on Computer Vision (ICCV), 2021
Comparison of Two Gradient Computation Methods in Python [paper]
Sri Hari Krishna Narayanan, Paul Hovland, Kshitij Kulshreshtha, Devashri Nagarkar, Kaitlyn MacIntyre, Riley Wagner, Deqing Fu.
Neural Information Processing Systems (NIPS) Autodiff Workshop, 2017