Luyu Gao

Artificial Intelligence · 2020–2026

A researcher in the Science corpus: 16 papers; trusts 631 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 469 citations into it; #5,790 of 35,345 by trust here, #3,052 by citations
• Natural Language Processing — 258 citations into it; #4,355 of 5,688 by trust here, #1,891 by citations
• Computer Vision and Pattern Recognition — 184 citations into it; #8,118 of 21,575 by trust here, #6,089 by citations
• Information Retrieval & Search — 172 citations into it; #198 of 1,022 by trust here, #284 by citations
• Large Language Models — 128 citations into it; #289 of 799 by trust here, #612 by citations
• Evaluation & Benchmarks — 93 citations into it
• Information Systems — 76 citations into it; #2,178 of 8,771 by trust here, #3,098 by citations
• Prompting & Reasoning — 49 citations into it

Whom Luyu Gao trusts overall

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

1. Zhuyun Dai
2. Geoffrey E. Hinton
3. Kenton C. T. Lee
4. Jacob Devlin
5. Yoshua Bengio
6. Ilya Sutskever
7. Diederik P. Kingma
8. Tomas Mikolov
9. Alex Krizhevsky
10. Jamie Callan

Who trusts Luyu Gao overall

1. Wayne Xin Zhao
2. Jamie Callan
3. Sebastian Hofstätter
4. Niklas Muennighoff
5. Jimmy J. Lin
6. Sheng-Chieh Lin
7. Jing Liu
8. Ruiyang Ren
9. Shitao Xiao
10. Omar Khattab

Papers from Luyu Gao's perspective

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

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

Their papers

• Self-Refine: Iterative Refinement with Self-Feedback (2023) — 4,061 citations
• PAL: Program-aided Language Models (2022) — 774 citations
• Attributed Text Generation via Post-hoc Research and Revision (2022) — 27 citations
• Active Retrieval Augmented Generation (2023) — 758 citations
• Condenser: a Pre-training Architecture for Dense Retrieval (2021) — 308 citations
• RARR: Researching and Revising What Language Models Say, Using Language Models (2022) — 339 citations
• COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List (2021) — 275 citations
• Precise Zero-Shot Dense Retrieval without Relevance Labels (2022) — 788 citations
• Understanding BERT Rankers Under Distillation (2020) — 58 citations
• Tevatron Meets Megatron: Expert-Parallel LLM Reranker Training on an Academic Budget (2026)
• Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer (2022) — 53 citations
• Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval (2021) — 395 citations
• Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup (2021) — 167 citations
• Complementing Lexical Retrieval with Semantic Residual Embedding (2020) — 91 citations
• Modularized Transfomer-based Ranking Framework (2020) — 49 citations
• EARL: Speedup Transformer-based Rankers with Pre-computed Representation (2020) — 9 citations