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2020 – today
- 2024
[c13]Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica:
LLM-Assisted Code Cleaning For Training Accurate Code Generators. ICLR 2024- [c12]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:
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. ICLR 2024 - [c11]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:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. ICML 2024 - [c10]Zhanghao Wu, Wei-Lin Chiang, Ziming Mao, Zongheng Yang, Eric J. Friedman, Scott Shenker, Ion Stoica:
Can't Be Late: Optimizing Spot Instance Savings under Deadlines. NSDI 2024: 185-203 - [i11]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. CoRR abs/2403.04132 (2024) - [i10]Tyler Griggs, Xiaoxuan Liu, Jiaxiang Yu, Doyoung Kim, Wei-Lin Chiang, Alvin Cheung, Ion Stoica:
M\'elange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity. CoRR abs/2404.14527 (2024) - [i9]Justin Cui, Wei-Lin Chiang, Ion Stoica, Cho-Jui Hsieh:
OR-Bench: An Over-Refusal Benchmark for Large Language Models. CoRR abs/2405.20947 (2024) - [i8]Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. CoRR abs/2406.11939 (2024) - [i7]Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M. Waleed Kadous, Ion Stoica:
RouteLLM: Learning to Route LLMs with Preference Data. CoRR abs/2406.18665 (2024) - 2023
- [c9]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:
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. NeurIPS 2023 - [c8]Zongheng Yang, Zhanghao Wu, Michael Luo, Wei-Lin Chiang, Romil Bhardwaj, Woosuk Kwon, Siyuan Zhuang, Frank Sifei Luan, Gautam Mittal, Scott Shenker, Ion Stoica:
SkyPilot: An Intercloud Broker for Sky Computing. NSDI 2023: 437-455 - [i6]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:
Judging LLM-as-a-judge with MT-Bench and Chatbot Arena. CoRR abs/2306.05685 (2023) - [i5]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:
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. CoRR abs/2309.11998 (2023) - [i4]Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica:
Rethinking Benchmark and Contamination for Language Models with Rephrased Samples. CoRR abs/2311.04850 (2023) - [i3]Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica:
LLM-Assisted Code Cleaning For Training Accurate Code Generators. CoRR abs/2311.14904 (2023) - 2022
- [c7]Zongheng Yang, Wei-Lin Chiang, Sifei Luan, Gautam Mittal, Michael Luo, Ion Stoica:
Balsa: Learning a Query Optimizer Without Expert Demonstrations. SIGMOD Conference 2022: 931-944 - [i2]Zongheng Yang, Wei-Lin Chiang, Sifei Luan, Gautam Mittal, Michael Luo, Ion Stoica:
Balsa: Learning a Query Optimizer Without Expert Demonstrations. CoRR abs/2201.01441 (2022) - 2020
- [c6]Yu-Sheng Li, Wei-Lin Chiang, Ching-Pei Lee:
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization. ICML 2020: 5842-5852
2010 – 2019
- 2019
- [c5]Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh:
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. KDD 2019: 257-266 - [i1]Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh:
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. CoRR abs/1905.07953 (2019) - 2018
- [c4]Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin:
Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification. ACML 2018: 312-326 - [c3]Wei-Lin Chiang, Yu-Sheng Li, Ching-Pei Lee, Chih-Jen Lin:
Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification. SDM 2018: 504-512 - 2016
- [c2]Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin:
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments. KDD 2016: 1485-1494 - 2015
- [c1]Mu-Chu Lee, Wei-Lin Chiang, Chih-Jen Lin:
Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems. ICDM 2015: 835-840
Coauthor Index
aka: Joseph E. Gonzalez
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last updated on 2024-09-04 00:30 CEST by the dblp team
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