影响力指数
97.75/100
前 0.1%
全站排名 #66
发表论文41
平均评分5.9
年均产出13.7 篇/年

Simon Shaolei Du

Assistant Professor@University of Washington·美国·OpenReview
研究方向

representation learning theory · reinforcement learning theory · non-convex optimization · deep learning theory

7.8
17

Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination

ICML 2025Oral
7.8
17

Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs

NeurIPS 2025Poster
通讯
7.3
19

Reinforcement Learning for Reasoning in Large Language Models with One Training Example

NeurIPS 2025Poster
7.1
31

A Minimalist Example of Edge-of-Stability and Progressive Sharpening

NeurIPS 2025Poster
三作
7.0
22

Extragradient Preference Optimization (EGPO): Beyond Last-Iterate Convergence for Nash Learning from Human Feedback

COLM 2025Poster
三作
6.8
21

Deployment Efficient Reward-Free Exploration with Linear Function Approximation

NeurIPS 2025Poster
6.8
20

Transformers are Efficient Compilers, Provably

COLM 2025Poster
通讯
6.5
16

LoRe: Personalizing LLMs via Low-Rank Reward Modeling

COLM 2025Poster
6.4
33

Understanding the Gain from Data Filtering in Multimodal Contrastive Learning

NeurIPS 2025Poster
三作
6.4
24

Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval

NeurIPS 2025Poster
三作
6.1
12

Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback

ICML 2025Poster
6.0
23

The Crucial Role of Samplers in Online Direct Preference Optimization

ICLR 2025Poster
三作
5.5
15

Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback

ICLR 2025Rejected
5.3
25

Multi-Agent Reinforcement Learning from Human Feedback: Data Coverage and Algorithmic Techniques

ICLR 2025Rejected
通讯
4.8
20

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters

ICLR 2025Rejected
4.8
12

Deployment Efficient Reward-Free Exploration with Linear Function Approximation

ICLR 2025Rejected
4.5
26

On Erroneous Agreements of CLIP Image Embeddings

ICLR 2025Rejected
三作
3.8
14

Transformers are Efficient Compilers, Provably

ICLR 2025Rejected
通讯