Wei-Lin Chiang

According to our database, Wei-Lin Chiang authored at least 20 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SkyServe: Serving AI Models across Regions and Clouds with Spot Instances.

Ziming Mao, Tian Xia, Zhanghao Wu, Wei-Lin Chiang, Tyler Griggs, Romil Bhardwaj, Zongheng Yang, Scott Shenker, Ion Stoica

CoRR, 2024

How to Evaluate Reward Models for RLHF.

Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios N. Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica

CoRR, 2024

RouteLLM: Learning to Route LLMs with Preference Data.

Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M. Waleed Kadous, Ion Stoica

CoRR, 2024

From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica

CoRR, 2024

OR-Bench: An Over-Refusal Benchmark for Large Language Models.

Justin Cui, Wei-Lin Chiang, Ion Stoica, Cho-Jui Hsieh

CoRR, 2024

M\'elange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity.

Tyler Griggs, Xiaoxuan Liu, Jiaxiang Yu, Doyoung Kim, Wei-Lin Chiang, Alvin Cheung, Ion Stoica

CoRR, 2024

Can't Be Late: Optimizing Spot Instance Savings under Deadlines.

Zhanghao Wu, Wei-Lin Chiang, Ziming Mao, Zongheng Yang, Eric J. Friedman, Scott Shenker, Ion Stoica

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

LLM-Assisted Code Cleaning For Training Accurate Code Generators.

Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Rethinking Benchmark and Contamination for Language Models with Rephrased Samples.

Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica

CoRR, 2023

SkyPilot: An Intercloud Broker for Sky Computing.

Zongheng Yang, Zhanghao Wu, Michael Luo, Wei-Lin Chiang, Romil Bhardwaj, Woosuk Kwon, Siyuan Zhuang, Frank Sifei Luan, Gautam Mittal, Scott Shenker, Ion Stoica

Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Balsa: Learning a Query Optimizer Without Expert Demonstrations.

Zongheng Yang, Wei-Lin Chiang, Sifei Luan, Gautam Mittal, Michael Luo, Ion Stoica

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2020

Manifold Identification for Ultimately Communication-Efficient Distributed Optimization.

Yu-Sheng Li, Wei-Lin Chiang, Ching-Pei Lee

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.

Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification.

Wei-Lin Chiang, Yu-Sheng Li, Ching-Pei Lee, Chih-Jen Lin

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification.

Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin

Proceedings of The 10th Asian Conference on Machine Learning, 2018

2016

Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments.

Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems.

Mu-Chu Lee, Wei-Lin Chiang, Chih-Jen Lin

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015