Li, Daliang

Understanding Robustness of Transformers for Image Classification

Bhojanapalli, S., Chakrabarti, A., Glasner, D., Li, D., Unterthiner, T., & Veit, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 440

On information loss in AdS3/CFT2

Fitzpatrick, A. L., Kaplan, J., Li, D., & Wang, J. (2016) · Journal of High Energy Physics

Black Holes and Theoretical PhysicsAlgebraic structures and combinatorial models

Cited by 129

Modifying Memories in Transformer Models

Zhu, C., Rawat, A. S., Zaheer, M., Bhojanapalli, S., Li, D., Yu, F., & Kumar, S. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 48

Large Language Models with Controllable Working Memory

Li, D., Rawat, A. S., Zaheer, M., Wang, X., Lukasik, M., Veit, A., Yu, F., & Kumar, S. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingNatural Language Processing Techniques

Cited by 46

Degenerate operators and the 1/c expansion: Lorentzian resummations, high order computations, and super-Virasoro blocks

Chen, H., Fitzpatrick, A. L., Kaplan, J., Li, D., & Wang, J. (2017) · Journal of High Energy Physics

Black Holes and Theoretical PhysicsAlgebraic structures and combinatorial models

Cited by 40