Deshraj Yadav
Computer Vision and Pattern Recognition · 2016–2025
A researcher in the Science corpus: 6 papers; trusts 332 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 136 citations into it; #6,207 of 21,575 by trust here, #3,111 by citations
- Artificial Intelligence — 126 citations into it; #11,300 of 35,345 by trust here, #3,757 by citations
- Natural Language Processing — 60 citations into it; #2,925 of 5,688 by trust here, #1,150 by citations
- Multimodal Learning — 47 citations into it; #468 of 1,211 by trust here, #301 by citations
- Model Architectures — 15 citations into it
- Safety, Robustness & Interpretability — 12 citations into it
Whom Deshraj Yadav trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Karen Simonyan
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Andrew Zisserman
- Ross B. Girshick
- Yann LeCun
Who trusts Deshraj Yadav overall
- Kalpesh Krishna
- Shikib Mehri
- Weihao Yu
- Muthu Kumar Chandrasekaran
- Harsh Agrawal
- David Schlangen
- Zhe Gan
- Fabio Petroni
- Matt Deitke
- Dhruv Batra
Papers from Deshraj Yadav's perspective
Ordered by how strongly the researchers Deshraj Yadav trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Visual Dialog (2016) — 1,102 citations
- EvalAI: Towards Better Evaluation Systems for AI Agents (2019) — 77 citations
- Do explanations make VQA models more predictable to a human? (2018) — 105 citations
- It Takes Two to Tango: Towards Theory of AI's Mind (2017) — 58 citations
- Evaluating Visual Conversational Agents via Cooperative Human-AI Games (2017) — 80 citations
- Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory (2025) — 478 citations