Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner

Hanwen Zhong, Jiaxin Chen, Yutong Zhang, Di Huang, Yunhong Wang
2/3/2026

No confident code implementation found for this paper. 1 possible match can be shown below.

Semantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Revisiting Visual Model Robustness: A Frequency Long-Tailed Distribution View

100% match2026

Building Timeseries Dataset: Empowering Large-Scale Building Analytics

100% match2026

Boundary Matters: A Bi-Level Active Finetuning Method

100% match1 repo142026

Fake It Until You Make It : Towards Accurate Near-Distribution Novelty Detection

100% match2026

Prompt3D: Random Prompt Assisted Weakly-Supervised 3D Object Detection

100% match1 repo82026

Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration

100% match2026

Cite this paper

@article{zhong2026transforming,
  title  = {Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner},
  author = {Hanwen Zhong and Jiaxin Chen and Yutong Zhang and Di Huang and Yunhong Wang},
  year   = {2026},
  url    = {https://www.semanticscholar.org/paper/678e45da466f2998002cfda2e5deae012a9aea49},
  journal = {NEURIPS 2024 2024}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/678e45da466f2998002cfda2e5deae012a9aea49.svg)](https://codeofpaper.com/paper/678e45da466f2998002cfda2e5deae012a9aea49)

Discussion