Jinlan Fu
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 10 papers; trusts 458 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 432 citations into it; #14,505 of 35,345 by trust here, #3,146 by citations
- Natural Language Processing — 337 citations into it; #2,385 of 5,688 by trust here, #768 by citations
- Computer Vision and Pattern Recognition — 138 citations into it
- Evaluation & Benchmarks — 105 citations into it; #1,631 of 3,147 by trust here, #1,383 by citations
- Large Language Models — 103 citations into it
- Representation & Self-Supervised Learning — 47 citations into it
- Model Architectures — 44 citations into it
- Prompting & Reasoning — 39 citations into it; #204 of 359 by trust here, #102 by citations
Whom Jinlan Fu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- Alex Graves
- Richard Socher
- Sepp Hochreiter
- Kaiming He
Who trusts Jinlan Fu overall
- Pengfei Liu
- Yixin Liu
- See-Kiong Ng
- Yang Liu
- Potsawee Manakul
- Weizhe Yuan
- Yanghua Xiao
- Sebastian Ruder
- Yuheng Zha
- Xuanjing Huang
Papers from Jinlan Fu's perspective
Ordered by how strongly the researchers Jinlan Fu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing (2021) — 5,562 citations
- XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation (2021) — 234 citations
- ExplainaBoard: An Explainable Leaderboard for NLP (2021) — 61 citations
- DataLab: A Platform for Data Analysis and Intervention (2022) — 14 citations
- SpanNER: Named Entity Re-/Recognition as Span Prediction (2021) — 134 citations
- GPTScore: Evaluate as You Desire (2023) — 485 citations
- Polyglot Prompt: Multilingual Multitask PrompTraining (2022) — 16 citations
- A Knowledge-Aware Sequence-to-Tree Network for Math Word Problem Solving (2020) — 80 citations
- Interpretable Multi-dataset Evaluation for Named Entity Recognition (2020) — 49 citations
- Adaptive Co-attention Network for Named Entity Recognition in Tweets (2018) — 425 citations