Linxi (Jim) Fan

Artificial Intelligence · 2014–2025

A researcher in the Science corpus: 13 papers; trusts 434 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 482 citations into it
• Computer Vision and Pattern Recognition — 335 citations into it
• Reinforcement Learning — 191 citations into it; #2,195 of 2,242 by trust here, #1,519 by citations
• Control and Systems Engineering — 117 citations into it
• Robotics & Control — 90 citations into it; #578 of 609 by trust here, #214 by citations
• Model Architectures — 63 citations into it
• Evaluation & Benchmarks — 60 citations into it; #3,010 of 3,147 by trust here, #2,166 by citations
• Large Language Models — 58 citations into it

Whom Linxi (Jim) Fan trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. Sergey Levine
9. Ross B. Girshick
10. Sepp Hochreiter

Who trusts Linxi (Jim) Fan overall

1. Ajay Mandlekar
2. Jonathan Booher
3. Rohan Chitnis
4. Yuke Zhu
5. Guanzhi Wang
6. German Ignacio Parisi
7. Danijar Hafner
8. Amir Ghodrati
9. Luca Weihs
10. Shuyan Zhou

Papers from Linxi (Jim) Fan's perspective

Ordered by how strongly the researchers Linxi (Jim) Fan trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• VIMA: General Robot Manipulation with Multimodal Prompts (2022) — 578 citations
• MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge (2022) — 597 citations
• RubiksNet: Learnable 3D-Shift for Efficient Video Action Recognition (2020) — 73 citations
• Voyager: An Open-Ended Embodied Agent with Large Language Models (2023) — 1,998 citations
• iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes (2020) — 246 citations
• MimicPlay: Long-Horizon Imitation Learning by Watching Human Play (2023) — 343 citations
• GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models (2025) — 393 citations
• LongVILA: Scaling Long-Context Visual Language Models for Long Videos (2024) — 306 citations
• MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations (2023) — 398 citations
• SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark (2018) — 167 citations
• World of Bits: An Open-Domain Platform for Web-Based Agents (2017) — 341 citations
• Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin (2015) — 3,177 citations
• How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets (2014) — 66 citations