Daya Guo
Artificial Intelligence · 2019–2026
A researcher in the Science corpus: 17 papers; trusts 221 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 436 citations into it; #23,069 of 35,345 by trust here, #2,245 by citations
- Natural Language Processing — 251 citations into it; #3,424 of 5,688 by trust here, #690 by citations
- Information Systems — 175 citations into it; #2,439 of 8,771 by trust here, #93 by citations
- Evaluation & Benchmarks — 142 citations into it
- Large Language Models — 131 citations into it; #537 of 799 by trust here, #236 by citations
- Computer Vision and Pattern Recognition — 111 citations into it
- Software — 95 citations into it; #812 of 1,227 by trust here, #26 by citations
- Code Generation & Program Synthesis — 78 citations into it
Whom Daya Guo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Miltiadis Allamanis
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Alec Radford
- Sepp Hochreiter
- Kaiming He
- Yann LeCun
Who trusts Daya Guo overall
- Yue Wang
- Chun Xia
- Baptiste Rozière
- Yichen Xu
- Toufique Ahmed
- Shuai Lu
- Shuo Ren
- Prem Devanbu
- Tianyang Liu
- Hung Le
Papers from Daya Guo's perspective
Ordered by how strongly the researchers Daya Guo 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)
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- 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
Their papers
- CodeBERT: A Pre-Trained Model for Programming and Natural Languages (2020) — 4,078 citations
- DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning (2025) — 5,477 citations
- GraphCodeBERT: Pre-training Code Representations with Data Flow (2020) — 1,778 citations
- DeepSeek-Coder: When the Large Language Model Meets Programming - The Rise of Code Intelligence (2024) — 1,786 citations
- DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model (2024) — 1,318 citations
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models (2024) — 7,648 citations
- Analytical Reasoning of Text (2022) — 27 citations
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence (2026) — 347 citations
- DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence (2024) — 469 citations
- DeepSeek-V3 Technical Report (2024) — 3,725 citations
- DeepSeek LLM: Scaling Open-Source Language Models with Longtermism (2024) — 805 citations
- LongCoder: A Long-Range Pre-trained Language Model for Code Completion (2023) — 166 citations
- UniXcoder: Unified Cross-Modal Pre-training for Code Representation (2022) — 1,023 citations
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation (2021) — 1,545 citations
- Learning to Generate Code Sketches (2021) — 4 citations
- CodeBLEU: a Method for Automatic Evaluation of Code Synthesis (2020) — 902 citations
- Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing (2019) — 50 citations