Lianmin Zheng

Artificial Intelligence · 2017–2024

A researcher in the Science corpus: 14 papers; trusts 75 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 353 citations into it; #35,231 of 35,345 by trust here, #2,150 by citations
• Computer Vision and Pattern Recognition — 160 citations into it
• Efficiency & Compression — 126 citations into it
• Large Language Models — 114 citations into it
• Natural Language Processing — 55 citations into it
• Model Architectures — 54 citations into it
• Optimization & Training — 49 citations into it
• ML Systems & Hardware — 41 citations into it

Whom Lianmin Zheng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Ilya Sutskever
6. Diederik P. Kingma
7. Yann LeCun
8. Oriol Vinyals
9. Tianqi Chen
10. Richard S. Sutton

Who trusts Lianmin Zheng overall

1. Bill Yuchen Lin
2. Yuhui Li
3. Penghao Wu
4. Seungone Kim
5. Jiechuan Jiang
6. Wei-Lin Chiang
7. Nathan Lambert
8. Yaodong Yang
9. Jinjie Ni
10. Peiyi Wang

Papers from Lianmin Zheng's perspective

Ordered by how strongly the researchers Lianmin Zheng trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Judging LLM-as-a-judge with MT-Bench and Chatbot Arena (2023) — 9,887 citations
• LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset (2023) — 484 citations
• Efficient Memory Management for Large Language Model Serving with PagedAttention (2023) — 7,142 citations
• TVM: An Automated End-to-End Optimizing Compiler for Deep Learning (2018) — 357 citations
• High-throughput Generative Inference of Large Language Models with a Single GPU (2023) — 797 citations
• Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference (2024) — 1,398 citations
• Rethinking Benchmark and Contamination for Language Models with Rephrased Samples (2023) — 215 citations
• H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models (2023) — 817 citations
• SGLang: Efficient Execution of Structured Language Model Programs (2023) — 1,077 citations
• Ansor : Generating High-Performance Tensor Programs for Deep Learning (2020) — 585 citations
• Learning to Optimize Tensor Programs (2018) — 501 citations
• MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence (2017) — 248 citations
• This paper is included in the Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation.
• AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving