Yuxiao Dong
Artificial Intelligence · 2016–2025
A researcher in the Science corpus: 29 papers; trusts 632 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 871 citations into it; #5,269 of 35,345 by trust here, #1,693 by citations
- Computer Vision and Pattern Recognition — 420 citations into it; #16,613 of 21,575 by trust here, #3,345 by citations
- Large Language Models — 212 citations into it
- Natural Language Processing — 200 citations into it
- Graph Learning — 186 citations into it; #597 of 693 by trust here, #380 by citations
- Statistical and Nonlinear Physics — 148 citations into it; #1,740 of 10,127 by trust here, #724 by citations
- Evaluation & Benchmarks — 146 citations into it
- Information Systems — 135 citations into it; #4,994 of 8,771 by trust here, #801 by citations
Whom Yuxiao Dong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Kaiming He
- Ilya Sutskever
- Alex Krizhevsky
- Tomas Mikolov
- Jure Leskovec
- Yann LeCun
- Yizhou Sun
Who trusts Yuxiao Dong overall
- Chuan Shi
- Xiao Liu
- Xiao Wang
- Yuhui Ding
- Weihua Hu
- Liye Ma
- Ziniu Hu
- Chuxu Zhang
- Shirui Pan
- Hongxia Yang
Papers from Yuxiao Dong's perspective
Ordered by how strongly the researchers Yuxiao Dong 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
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- GLM-130B: An Open Bilingual Pre-trained Model (2022) — 1,288 citations
- ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation (2023) — 1,142 citations
- CogVLM: Visual Expert for Pretrained Language Models (2023) — 827 citations
- Heterogeneous Graph Transformer (2020) — 1,684 citations
- Microsoft Academic Graph: When experts are not enough (2020) — 697 citations
- GraphMAE: Self-Supervised Masked Graph Autoencoders (2022) — 977 citations
- Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec (2017) — 987 citations
- OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs (2021) — 508 citations
- metapath2vec: Scalable Representation Learning for Heterogeneous Networks (2017) — 2,469 citations
- CogAgent: A Visual Language Model for GUI Agents (2023) — 804 citations
- CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer (2024) — 2,147 citations
- AgentTuning: Enabling Generalized Agent Abilities for LLMs (2023) — 347 citations
- AgentBench: Evaluating LLMs as Agents (2023) — 1,063 citations
- OAG: Toward Linking Large-scale Heterogeneous Entity Graphs (2019) — 133 citations
- GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning (2025) — 313 citations
- LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks (2024) — 310 citations
- LVBench: An Extreme Long Video Understanding Benchmark (2024) — 399 citations
- ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools (2024) — 1,646 citations
- ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search (2024) — 491 citations
- LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding (2023) — 1,466 citations