Evan Zhang — accepted AI-conference papers

2026

Flow Autoencoders are Effective Protein Tokenizers

Rohit Dilip, Evan Zhang, Ayush Varshney, David Van Valen

ICLR 2026poster

Protein structure tokenizers enable the creation of multimodal models of protein structure, sequence, and function. Current approaches to protein structure tokenization rely on bespoke components that are invariant to spatial symmetries, but that are challenging to optimize and scale. We present Kan…

Cited by 0 Source ↗code ↗Scholar ↗

2024

Multi-Task Interactive Robot Fleet Learning with Visual World Models

Huihan Liu, Yu Zhang, Vaarij Betala, Evan Zhang, James Liu, Crystal Ding +1

CoRL 2024poster

Recent advancements in large-scale multi-task robot learning offer the potential for deploying robot fleets in household and industrial settings, enabling them to perform diverse tasks across various environments. However, AI-enabled robots often face challenges with generalization and robustness wh…

Cited by 4 Source ↗code ↗Scholar ↗