Xianpei Han

Artificial Intelligence · 2005–2024

A researcher in the Science corpus: 12 papers; trusts 283 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 247 citations into it; #10,169 of 35,345 by trust here, #9,465 by citations
• Natural Language Processing — 128 citations into it
• Computer Vision and Pattern Recognition — 76 citations into it; #9,727 of 21,575 by trust here, #11,950 by citations
• Large Language Models — 43 citations into it
• Information Retrieval & Search — 37 citations into it
• Information Systems — 36 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Model Architectures — 23 citations into it

Whom Xianpei Han trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Luke S. Zettlemoyer
6. Alex Krizhevsky
7. Percy Liang
8. Yann LeCun
9. Kyunghyun Cho
10. Dzmitry Bahdanau

Who trusts Xianpei Han overall

1. Zhaochen Guo
2. Denilson Barbosa
3. Francesco Piccinno
4. Wei Shen
5. Changbin Liu
6. Ben Hachey
7. Zheng Fang
8. Robert West
9. Zhuang Li
10. Paolo Ferragina

Papers from Xianpei Han's perspective

Ordered by how strongly the researchers Xianpei Han 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Collective entity linking in web text: a graph-based method (2011) — 424 citations
• Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision (2021) — 5 citations
• Benchmarking Large Language Models in Retrieval-Augmented Generation (2023) — 594 citations
• Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction (2021) — 338 citations
• CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction (2018) — 370 citations
• ShortGPT: Layers in Large Language Models are More Redundant Than You Expect (2024) — 376 citations
• ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases (2023) — 387 citations
• Unified Structure Generation for Universal Information Extraction (2022) — 620 citations
• BERT-QE: Contextualized Query Expansion for Document Re-ranking (2020) — 121 citations
• CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain (2019) — 82 citations
• Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing (2018) — 85 citations
• Dynamic open spectrum sharing MAC protocol for wireless ad hoc networks (2005) — 383 citations