Peiyi Wang
Artificial Intelligence · with Zhang · 2022–2026
A researcher in the Science corpus: 8 papers; trusts 49 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 219 citations into it
- Large Language Models — 91 citations into it
- Natural Language Processing — 57 citations into it
- Evaluation & Benchmarks — 53 citations into it
- Computer Vision and Pattern Recognition — 46 citations into it
- Model Architectures — 18 citations into it
- Computer Networks and Communications — 16 citations into it
- Hardware and Architecture — 10 citations into it
Whom Peiyi Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Jason Wei
- Xuezhi Wang
- Chin-Yew Lin
Who trusts Peiyi Wang overall
- Zhihong Shao
- Minghao Wu
- Weihao Zeng
- Anisha Gunjal
- Mengzhou Xia
- ES Shahul
- Lichang Chen
- Ming Li
- Yufei Wang
- Alham Fikri Aji
Papers from Peiyi Wang's perspective
Ordered by how strongly the researchers Peiyi Wang 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)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- 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
- 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)
Their papers
- Large Language Models are not Fair Evaluators (2023) — 1,116 citations
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models (2024) — 7,648 citations
- Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation (2022) — 189 citations
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence (2026) — 347 citations
- Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding (2024) — 297 citations
- DeepSeek LLM: Scaling Open-Source Language Models with Longtermism (2024) — 805 citations
- Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations (2023) — 1,036 citations
- Making Large Language Models Better Reasoners with Alignment (2023) — 91 citations