Haoran Li

Artificial Intelligence · with Mehdad · 2019–2022

A researcher in the Science corpus: 6 papers; trusts 145 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 153 citations into it
• Natural Language Processing — 143 citations into it; #5,075 of 5,688 by trust here, #2,243 by citations
• Computer Vision and Pattern Recognition — 42 citations into it
• Evaluation & Benchmarks — 36 citations into it
• Representation & Self-Supervised Learning — 34 citations into it
• Large Language Models — 27 citations into it
• Optimization & Training — 7 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Haoran Li trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Ilya Sutskever
5. Alex Krizhevsky
6. Tomas Mikolov
7. Yann LeCun
8. Kaiming He
9. Alex Graves
10. Jimmy Ba

Who trusts Haoran Li overall

1. Panupong Pasupat
2. Ohad Rubin
3. Genta Indra Winata
4. Jonathan Herzig
5. Yuan Zhang
6. Andrea Madotto

Papers from Haoran Li's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark (2020) — 223 citations
• Emerging Cross-lingual Structure in Pretrained Language Models (2019) — 329 citations
• You Don’t Know My Favorite Color: Preventing Dialogue Representations from Revealing Speakers’ Private Personas (2022) — 23 citations
• CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning (2021) — 72 citations
• General Purpose Text Embeddings from Pre-trained Language Models for Scalable Inference (2020) — 10 citations
• Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation (2020) — 104 citations