Xinyang Geng

Artificial Intelligence · 2016–2025

A researcher in the Science corpus: 6 papers; trusts 310 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 105 citations into it; #18,021 of 35,345 by trust here, #9,170 by citations
• Computer Vision and Pattern Recognition — 82 citations into it; #9,863 of 21,575 by trust here, #5,565 by citations
• Reinforcement Learning — 50 citations into it
• Meta & Continual Learning — 20 citations into it
• Control and Systems Engineering — 19 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Optimization & Training — 14 citations into it
• Generative Models — 10 citations into it

Whom Xinyang Geng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Sergey Levine
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yann LeCun
8. Chelsea Finn
9. Pieter Abbeel
10. J. Urgen Schmidhuber

Who trusts Xinyang Geng overall

1. Cédric Colas
2. Lei Tai
3. Sanmit Narvekar
4. Benjamin Eysenbach
5. Rui Wang
6. Sergey Levine
7. Vitchyr H. Pong
8. Jemin Hwangbo
9. R. Li
10. Glen Berseth

Papers from Xinyang Geng's perspective

Ordered by how strongly the researchers Xinyang Geng trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Real-time user-guided image colorization with learned deep priors (2017) — 633 citations
• Automatic Goal Generation for Reinforcement Learning Agents (2017) — 582 citations
• The False Promise of Imitating Proprietary LLMs (2023) — 280 citations
• Deep reinforcement learning for tensegrity robot locomotion (2016) — 106 citations
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
• Variable-Shot Adaptation for Online Meta-Learning (2020) — 4 citations