Zhengxiao Du
Artificial Intelligence · 2021–2025
A researcher in the Science corpus: 12 papers; trusts 163 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 436 citations into it; #22,077 of 35,345 by trust here, #2,275 by citations
- Large Language Models — 197 citations into it; #388 of 799 by trust here, #265 by citations
- Natural Language Processing — 196 citations into it
- Computer Vision and Pattern Recognition — 188 citations into it
- Evaluation & Benchmarks — 123 citations into it
- Prompting & Reasoning — 73 citations into it
- Model Architectures — 48 citations into it
- Efficiency & Compression — 33 citations into it
Whom Zhengxiao Du trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Timo Schick
- Diederik P. Kingma
- Ilya Sutskever
- Alec Radford
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Jacob Devlin
Who trusts Zhengxiao Du overall
- Xiao Liu
- Ming Ding
- Hui Zeng
- Junyi Li
- Xu Han
- Jiahao Yu
- Xinyue Shen
- Chenguang Wang
- Yuxian Gu
- Aohan Zeng
Papers from Zhengxiao Du's perspective
Ordered by how strongly the researchers Zhengxiao Du trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- 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
- 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
- GLM-130B: An Open Bilingual Pre-trained Model (2022) — 1,288 citations
- P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks (2021) — 1,125 citations
- GPT Understands, Too (2021) — 1,460 citations
- GLM: General Language Model Pretraining with Autoregressive Blank Infilling (2021) — 1,956 citations
- WuDaoCorpora: A super large-scale Chinese corpora for pre-training language models (2021) — 131 citations
- AgentBench: Evaluating LLMs as Agents (2023) — 1,063 citations
- P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks (2022) — 1,117 citations
- GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning (2025) — 313 citations
- GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models (2025) — 393 citations
- ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools (2024) — 1,646 citations
- LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding (2023) — 1,466 citations
- All NLP Tasks Are Generation Tasks: A General Pretraining Framework (2021) — 68 citations