Long (Tony) Lian Long (Tony) Lian

I am an EECS PhD student at UC Berkeley and BAIR, advised by Prof. Adam Yala and Prof. Trevor Darrell. My research primarily focuses on developing LLMs/VLMs with reasoning capabilities through RL. I was an intern with the Deep Imagination Research team at NVIDIA Research. I hold a B.A. in Computer Science from UC Berkeley, where I conducted research under the supervision of Prof. Stella Yu during my undergraduate studies. I also interned with Baidu’s Distributed Deep Learning team.

Long (Tony) Lian

Publications (*: equal contribution)

CrossMAE: Rethinking Patch Dependence for Masked Autoencoders

Letian Fu*, Long Lian*, Renhao Wang, Baifeng Shi, Xudong Wang, Adam Yala†, Trevor Darrell†, Alexei A. Efros†, Ken Goldberg†

Transactions on Machine Learning Research (TMLR), 2025

CrossMAE: Rethinking Patch Dependence for Masked Autoencoders

Unsupervised Universal Image Segmentation

Dantong Niu*, Xudong Wang*, Xinyang Han*, Long Lian, Roei Herzig, Trevor Darrell

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Unsupervised Universal Image Segmentation

Self-correcting LLM-controlled Diffusion Models

Tsung-Han Wu*, Long Lian*, Joseph E Gonzalez, Boyi Li, Trevor Darrell

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Self-correcting LLM-controlled Diffusion Models

LLM-grounded Video Diffusion Models

Long Lian*, Baifeng Shi*, Adam Yala, Trevor Darrell, Boyi Li

International Conference on Learning Representations (ICLR), 2024

LLM-grounded Video Diffusion Models

LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models

Long Lian, Boyi Li, Adam Yala, Trevor Darrell

Transactions on Machine Learning Research (TMLR), 2024 (Featured Certification)

LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models

Q-Diffusion: Quantizing Diffusion Models

Xiuyu Li, Yijiang Liu, Long Lian, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer

International Conference on Computer Vision (ICCV), 2023

Q-Diffusion: Quantizing Diffusion Models

Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping

Long Lian, Zhirong Wu, Stella X. Yu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping

Unsupervised Selective Labeling for More Effective Semi-Supervised Learning

Xudong Wang*, Long Lian*, Stella X. Yu

European Conference on Computer Vision (ECCV), 2022

Unsupervised Selective Labeling for More Effective Semi-Supervised Learning

Debiased Learning from Naturally Imbalanced Pseudo-Labels

Xudong Wang, Zhirong Wu, Long Lian, Stella X. Yu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

Debiased Learning from Naturally Imbalanced Pseudo-Labels

Unsupervised Visual Attention and Invariance for Reinforcement Learning

Xudong Wang*, Long Lian*, Stella X. Yu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

Unsupervised Visual Attention and Invariance for Reinforcement Learning

Long-tailed Recognition by Routing Diverse Distribution-aware Experts

Xudong Wang, Long Lian, Zhongqi Miao, Ziwei Liu, Stella X. Yu

International Conference on Learning Representations (ICLR), 2021 (Spotlight)

Long-tailed Recognition by Routing Diverse Distribution-aware Experts

Academic Services

Reviewer for CVPR/ECCV/ICCV/ICLR/ICML/NeurIPS/AAAI

Side Projects

Stable Diffusion XL Demo WebUI

A gradio-based WebUI that allows playing around with SDXL locally and on Colab for free.

AnimeGAN.js

An implementation of AnimeGAN, which converts photos to anime style online, with tf.js.

Rainbow

An implementation of Rainbow algorithm with PARL reinforcement learning framework.