Quan Wei

Intern @MorganStanley | PhD student @UMNews | AI, Agent, RL

[Quan Wei @quanwei0]

@XMoney it sounds cool but I can’t find the money tab in the app.

[Hoi To Wai @hoitowai]

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models (https://t.co/2h4RSHN7hP) with @quanwei0 & @yauchungyiu on Wed 16 Jul 11am-1:30pm East Hall (3/3).

[Siliang Zeng @ZengSiliang]

Interesting project with @willcb @quanwei0 @Mingyi552237 and other collaborators. We show that turn-level credit assignment indeed helps a lot for multi-turn tasks.

Multi-turn task is the setting where we may think bringing MDP and other classic RL thoughts back to the table.

[will brown @willcb]

new paper with @ZengSiliang and other collaborators about some of our multi-turn findings from the past couple months :)

lots of experiments about the pros and cons of structured rewards and credit assignment, particularly relevant when doing tool-use RL with 7B models

[Chung Yiu Yau @yauchungyiu]

Our new quantization-aware training algorithm RoSTE can fine-tune quantized LLMs and break state-of-the-art benchmark accuracy on 4-bits Pythia, Qwen and Llama models! Thank you @quanwei0 for the great effort👏

Paper: https://t.co/ztc3jUjh7u
Code: https://t.co/UZpq9nyBUk

[IEEE ICASSP @ieeeICASSP]

"Large covariance matrix estimation with oracle statistical rate" by Quan Wei, Ziping Zhao https://t.co/FUktYjBSGt

[Quan Wei @quanwei0]

I am honored to receive the Best Student Paper Award at #ICASSP2023 with Prof. Ziping Zhao for our paper "Large covariance matrix estimation with oracle statistical rate"!