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Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?

In Submission Ranked 1st on AlpacaEval 2.0 Leaderboard (non-adversarial)

Wenzhe Li, Yong Lin, Mengzhou Xia, Chi Jin

Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?

FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning

ICML 2024, ICLR AGI Workshop 2024

Wenzhe Li, Zihan Ding, Seth Karten, Chi Jin

FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning

Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery

AAAI 2023 Oral Presentation

Yiqin Yang, Hao Hu, Wenzhe Li, Siyuan Li, Jun Yang, Qianchuan Zhao, Chongjie Zhang

Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL

NeurIPS 2022, L-DOD Workshop at RSS 2022

Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL

Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL

Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang

Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL

Offline Reinforcement Learning with Reverse Model-based Imagination

Jianhao Wang, Wenzhe Li, Haozhe Jiang, Guangxiang Zhu, Siyuan Li, Chongjie Zhang

Offline Reinforcement Learning with Reverse Model-based Imagination

Estimating High Order Gradients of the Data Distribution by Denoising

Chenlin Meng, Yang Song, Wenzhe Li, Stefano Ermon

Estimating High Order Gradients of the Data Distribution by Denoising

Tractable Computation of Expected Kernels

Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck

Tractable Computation of Expected Kernels