Sachit Menon

Computer Vision and Pattern Recognition · 2020–2025

A researcher in the Science corpus: 5 papers; trusts 647 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 139 citations into it; #7,674 of 21,575 by trust here, #5,464 by citations
• Artificial Intelligence — 110 citations into it; #12,686 of 35,345 by trust here, #12,387 by citations
• Multimodal Learning — 43 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Large Language Models — 19 citations into it; #362 of 799 by trust here, #746 by citations
• Safety, Robustness & Interpretability — 19 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Natural Language Processing — 13 citations into it

Whom Sachit Menon trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Karen Simonyan
5. Diederik P. Kingma
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Andrew Zisserman
10. Ross B. Girshick

Who trusts Sachit Menon overall

1. Sarah Pratt
2. Xintao Wang
3. Chitwan Saharia
4. Anurag Roy
5. Jingyi Zhang
6. Varun A. Kelkar
7. Peihao Zhu
8. Andreas Lugmayr
9. Kyoungkook Kang
10. Yuval Alaluf

Papers from Sachit Menon's perspective

Ordered by how strongly the researchers Sachit Menon 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. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models (2020) — 648 citations
• ViperGPT: Visual Inference via Python Execution for Reasoning (2023) — 823 citations
• Visual Classification via Description from Large Language Models (2022) — 411 citations
• Doubly Right Object Recognition: A Why Prompt for Visual Rationales (2022) — 40 citations
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations