Yi Li
Information Systems · IEEE Working Conference on Mining Software Repositories · 2019–2021
A researcher in the Science corpus: 4 papers; trusts 71 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 50 citations into it; #4,304 of 8,771 by trust here, #4,885 by citations
- Software — 46 citations into it; #690 of 1,227 by trust here, #718 by citations
- Artificial Intelligence — 22 citations into it
- Signal Processing — 22 citations into it
- Natural Language Processing — 16 citations into it
- Program Analysis & Verification — 15 citations into it; #255 of 301 by trust here, #274 by citations
- Code Generation & Program Synthesis — 9 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
Whom Yi Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Richard Socher
- Ilya Sutskever
- Fan Long
- Yoshua Bengio
- Geoffrey E. Hinton
- Christopher D. Manning
- Yoon Kim
- Kai Sheng Tai
- Kyunghyun Cho
Who trusts Yi Li overall
Papers from Yi Li's perspective
Ordered by how strongly the researchers Yi Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- 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)
- 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)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Vulnerability detection with fine-grained interpretations (2021) — 349 citations
- A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries (2020) — 645 citations
- DLFix: Context-based Code Transformation Learning for Automated Program Repair (2020) — 319 citations
- Improving bug detection via context-based code representation learning and attention-based neural networks (2019) — 168 citations