Qiang Fu
Artificial Intelligence · 2009 Ninth IEEE International Conference on Data Mining · 2009–2022
A researcher in the Science corpus: 6 papers; trusts 85 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 196 citations into it
- Natural Language Processing — 128 citations into it
- Computer Vision and Pattern Recognition — 78 citations into it
- Large Language Models — 53 citations into it
- Information Systems — 28 citations into it; #2,581 of 8,771 by trust here, #4,885 by citations
- Model Architectures — 5 citations into it
Whom Qiang Fu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Alec Radford
- Alex Graves
- Jimmy Ba
Who trusts Qiang Fu overall
- Min Du
- Shilin He
- Vijayaraghavan Murali
- Van-Hoang Le
- Feifei Li
- Hongyu Zhang
- Qingwei Lin
- Jian-Guang Lou
- Pinjia He
- Swarat Chaudhuri
Papers from Qiang Fu's perspective
Ordered by how strongly the researchers Qiang Fu trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- 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
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- On the Advance of Making Language Models Better Reasoners (2022) — 162 citations
- Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models (2022) — 47 citations
- Reasoning Like Program Executors (2022) — 61 citations
- Making Language Models Better Reasoners with Step-Aware Verifier (2022) — 328 citations
- Mining Invariants from Console Logs for System Problem Detection (2010) — 395 citations
- Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis (2009) — 604 citations