Weizhu Chen

Technical Fellow and CVP, Microsoft AI

出版物

表示方法:

- Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena
  
  Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin 林庆维, Jianguang Lou, Shifeng Chen, Yansong Tang, Weizhu Chen
  
  July 2024
  
  Preprint
  
  Preprint
- AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
  
  Tong Wu, Zhihao Fan, Xiao Liu, Yeyun Gong, Yelong Shen, Jian Jiao, Hai-Tao Zheng, Juntao Li, zhongyu wei, Jian Guo, Nan Duan, Weizhu Chen
  
  NeurIPS 2023 | December 2023
  
  Publication
- LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
  
  Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
  
  ICLR 2024 | October 2023
  
  DOI PDF
- In-Context Learning Unlocked for Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou
  
  NeurIPS 2023 | October 2023
  
  Publication
- Meet in the Middle: A New Pre-training Paradigm
  
  Anh Nguyen, Nikos Karampatziakis, Weizhu Chen
  
  NeurIPS 2023 | October 2023
  
  Publication
- ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
  
  Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
  
  ICLR 2024 | September 2023
  
  DOI PDF
- Making Language Models Better Reasoners with Step-Aware Verifier
  
  Yifei Li, Zeqi Lin, Shizhuo Zhang, Qiang Fu, Bei Chen, Jian-Guang Lou, Weizhu Chen
  
  ACL 2023 | June 2023
  
  Publication
- Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
  
  Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
  
  11th International Conference on Learning Representations (ICLR 2023) | May 2023
  
  Publication
- Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
  
  NeurIPS 2023 | April 2023
  
  Publication
- LoRA: Low-Rank Adaptation of Large Language Models
  
  Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
  
  ICLR 2022 | April 2022
  
  Publication 動画 Github プロジェクト
- TAPEX: Table Pre-training via Learning a Neural SQL Executor
  
  Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou
  
  ICLR 2022 | April 2022
  
  Publication
- Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
  
  Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, David Farhi, Jakub Pachocki, Xiaodong Liu, Weizhu Chen, Jianfeng Gao
  
  NeurIPS 2021 | March 2022
  
  PDF Publication Github
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト
- Multi-Task Deep Neural Networks for Natural Language Understanding
  
  Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao
  
  ACL 2019 | June 2019
  
  Publication プロジェクト

- Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena
  
  Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin 林庆维, Jianguang Lou, Shifeng Chen, Yansong Tang, Weizhu Chen
  
  July 2024
  
  Preprint
  
  Preprint
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト
- AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
  
  Tong Wu, Zhihao Fan, Xiao Liu, Yeyun Gong, Yelong Shen, Jian Jiao, Hai-Tao Zheng, Juntao Li, zhongyu wei, Jian Guo, Nan Duan, Weizhu Chen
  
  NeurIPS 2023 | December 2023
  
  Publication
- LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
  
  Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
  
  ICLR 2024 | October 2023
  
  DOI PDF
- Meet in the Middle: A New Pre-training Paradigm
  
  Anh Nguyen, Nikos Karampatziakis, Weizhu Chen
  
  NeurIPS 2023 | October 2023
  
  Publication
- In-Context Learning Unlocked for Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou
  
  NeurIPS 2023 | October 2023
  
  Publication
- ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
  
  Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
  
  ICLR 2024 | September 2023
  
  DOI PDF
- Making Language Models Better Reasoners with Step-Aware Verifier
  
  Yifei Li, Zeqi Lin, Shizhuo Zhang, Qiang Fu, Bei Chen, Jian-Guang Lou, Weizhu Chen
  
  ACL 2023 | June 2023
  
  Publication
- Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
  
  Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
  
  11th International Conference on Learning Representations (ICLR 2023) | May 2023
  
  Publication
- Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
  
  NeurIPS 2023 | April 2023
  
  Publication
- TAPEX: Table Pre-training via Learning a Neural SQL Executor
  
  Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou
  
  ICLR 2022 | April 2022
  
  Publication
- LoRA: Low-Rank Adaptation of Large Language Models
  
  Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
  
  ICLR 2022 | April 2022
  
  Publication 動画 Github プロジェクト
- Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
  
  Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, David Farhi, Jakub Pachocki, Xiaodong Liu, Weizhu Chen, Jianfeng Gao
  
  NeurIPS 2021 | March 2022
  
  PDF Publication Github
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト
- Multi-Task Deep Neural Networks for Natural Language Understanding
  
  Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao
  
  ACL 2019 | June 2019
  
  Publication プロジェクト
- Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
  
  NeurIPS 2023 | April 2023
  
  Publication
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト
- Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
  
  Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
  
  11th International Conference on Learning Representations (ICLR 2023) | May 2023
  
  Publication
- LoRA: Low-Rank Adaptation of Large Language Models
  
  Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
  
  ICLR 2022 | April 2022
  
  Publication 動画 Github プロジェクト
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト

- Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena
  
  Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin 林庆维, Jianguang Lou, Shifeng Chen, Yansong Tang, Weizhu Chen
  
  July 2024
  
  Preprint
  
  Preprint
- AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
  
  Tong Wu, Zhihao Fan, Xiao Liu, Yeyun Gong, Yelong Shen, Jian Jiao, Hai-Tao Zheng, Juntao Li, zhongyu wei, Jian Guo, Nan Duan, Weizhu Chen
  
  NeurIPS 2023 | December 2023
  
  Publication
- LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
  
  Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
  
  ICLR 2024 | October 2023
  
  DOI PDF
- Meet in the Middle: A New Pre-training Paradigm
  
  Anh Nguyen, Nikos Karampatziakis, Weizhu Chen
  
  NeurIPS 2023 | October 2023
  
  Publication
- In-Context Learning Unlocked for Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou
  
  NeurIPS 2023 | October 2023
  
  Publication
- ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
  
  Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
  
  ICLR 2024 | September 2023
  
  DOI PDF
- Making Language Models Better Reasoners with Step-Aware Verifier
  
  Yifei Li, Zeqi Lin, Shizhuo Zhang, Qiang Fu, Bei Chen, Jian-Guang Lou, Weizhu Chen
  
  ACL 2023 | June 2023
  
  Publication
- Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
  
  Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
  
  11th International Conference on Learning Representations (ICLR 2023) | May 2023
  
  Publication
- Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
  
  Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
  
  NeurIPS 2023 | April 2023
  
  Publication
- TAPEX: Table Pre-training via Learning a Neural SQL Executor
  
  Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou
  
  ICLR 2022 | April 2022
  
  Publication
- LoRA: Low-Rank Adaptation of Large Language Models
  
  Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
  
  ICLR 2022 | April 2022
  
  Publication 動画 Github プロジェクト
- Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
  
  Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, David Farhi, Jakub Pachocki, Xiaodong Liu, Weizhu Chen, Jianfeng Gao
  
  NeurIPS 2021 | March 2022
  
  PDF Publication Github
- On the Variance of the Adaptive Learning Rate and Beyond
  
  Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han
  
  Eighth International Conference on Learning Representations (ICLR) | April 2020
  
  Publication PDF プロジェクト
- Multi-Task Deep Neural Networks for Natural Language Understanding
  
  Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao
  
  ACL 2019 | June 2019
  
  Publication プロジェクト

Weizhu Chen

出版物

Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena

AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

In-Context Learning Unlocked for Diffusion Models

Meet in the Middle: A New Pre-training Paradigm

ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

Making Language Models Better Reasoners with Step-Aware Verifier

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

LoRA: Low-Rank Adaptation of Large Language Models

TAPEX: Table Pre-training via Learning a Neural SQL Executor

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

On the Variance of the Adaptive Learning Rate and Beyond

Multi-Task Deep Neural Networks for Natural Language Understanding

Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena

On the Variance of the Adaptive Learning Rate and Beyond

AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Meet in the Middle: A New Pre-training Paradigm

In-Context Learning Unlocked for Diffusion Models

ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

Making Language Models Better Reasoners with Step-Aware Verifier

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

TAPEX: Table Pre-training via Learning a Neural SQL Executor

LoRA: Low-Rank Adaptation of Large Language Models

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

On the Variance of the Adaptive Learning Rate and Beyond

Multi-Task Deep Neural Networks for Natural Language Understanding

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

On the Variance of the Adaptive Learning Rate and Beyond

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

LoRA: Low-Rank Adaptation of Large Language Models

On the Variance of the Adaptive Learning Rate and Beyond

Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena

AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Meet in the Middle: A New Pre-training Paradigm

In-Context Learning Unlocked for Diffusion Models

ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

Making Language Models Better Reasoners with Step-Aware Verifier

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

TAPEX: Table Pre-training via Learning a Neural SQL Executor

LoRA: Low-Rank Adaptation of Large Language Models

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

On the Variance of the Adaptive Learning Rate and Beyond

Multi-Task Deep Neural Networks for Natural Language Understanding