Guangxuan Xiao

Artificial Intelligence · 2021–2024

A researcher in the Science corpus: 5 papers; trusts 98 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 120 citations into it; #25,176 of 35,345 by trust here, #10,207 by citations
• Computer Vision and Pattern Recognition — 95 citations into it
• Natural Language Processing — 35 citations into it
• Efficiency & Compression — 33 citations into it; #874 of 1,264 by trust here, #749 by citations
• Model Architectures — 32 citations into it
• Evaluation & Benchmarks — 31 citations into it
• Generative Models — 16 citations into it
• Hardware and Architecture — 5 citations into it

Whom Guangxuan Xiao trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Kaiming He
6. Yann LeCun
7. Ilya Sutskever
8. Jonathan Ho
9. Karen Simonyan
10. Ross B. Girshick

Who trusts Guangxuan Xiao overall

1. Tim Dettmers
2. Ji Lin
3. Zirui Liu
4. Elias Frantar
5. Saleh Ashkboos
6. Ying Sheng
7. Mingjie Sun
8. Jing Shi
9. Jiaming Tang
10. Zichang Liu

Papers from Guangxuan Xiao's perspective

Ordered by how strongly the researchers Guangxuan Xiao 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

• SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models (2022) — 1,734 citations
• Efficient Streaming Language Models with Attention Sinks (2023) — 2,131 citations
• Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference (2024) — 425 citations
• FastComposer: Tuning-Free Multi-subject Image Generation with Localized Attention (2023) — 405 citations
• Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks (2021) — 15 citations