Chenliang Li
Artificial Intelligence · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval · 2012–2022
A researcher in the Science corpus: 10 papers; trusts 520 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 308 citations into it; #26,073 of 35,345 by trust here, #14,438 by citations
- Natural Language Processing — 170 citations into it
- Information Systems — 86 citations into it; #5,949 of 8,771 by trust here, #5,713 by citations
- Computer Vision and Pattern Recognition — 79 citations into it
- Safety, Robustness & Interpretability — 39 citations into it
- Representation & Self-Supervised Learning — 36 citations into it
- Signal Processing — 34 citations into it
- Model Architectures — 33 citations into it
Whom Chenliang Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ruslan Salakhutdinov
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Ronan Collobert
- Tomas Mikolov
- Kaiming He
Who trusts Chenliang Li overall
Papers from Chenliang Li's perspective
Ordered by how strongly the researchers Chenliang Li trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification (2020) — 387 citations
- Knowledge Graph Contrastive Learning for Recommendation (2022) — 506 citations
- Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey (2019) — 601 citations
- A Capsule Network for Recommendation and Explaining What You Like and Dislike (2019) — 129 citations
- A Survey on Deep Learning for Named Entity Recognition (2018) — 1,494 citations
- A Context-Aware User-Item Representation Learning for Item Recommendation (2017) — 226 citations
- Topic Modeling for Short Texts with Auxiliary Word Embeddings (2016) — 318 citations
- Fine-grained location extraction from tweets with temporal awareness (2014) — 106 citations
- TwiNER: named entity recognition in targeted twitter stream (2012) — 297 citations
- Twevent: segment-based event detection from tweets (2012) — 375 citations