Arpit Mittal
Artificial Intelligence · 2011–2021
A researcher in the Science corpus: 7 papers; trusts 145 researchers and is trusted by 94 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 95 citations into it; #2,743 of 35,345 by trust here, #2,989 by citations
- Natural Language Processing — 88 citations into it; #749 of 5,688 by trust here, #700 by citations
- Evaluation & Benchmarks — 46 citations into it; #409 of 3,147 by trust here, #424 by citations
- Computer Vision and Pattern Recognition — 36 citations into it; #9,723 of 21,575 by trust here, #15,955 by citations
- Sociology and Political Science — 22 citations into it; #18,358 of 22,756 by trust here, #16,952 by citations
- Information Systems — 21 citations into it; #7,808 of 8,771 by trust here, #4,682 by citations
- Information Retrieval & Search — 15 citations into it
- Safety, Robustness & Interpretability — 15 citations into it; #1,956 of 2,251 by trust here, #2,078 by citations
Whom Arpit Mittal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pedro F. Felzenszwalb
- Jianguo Zhang
- C. Burges
- Navneet Dalal
- Ross B. Girshick
- Lubomir D. Bourdev
- Geoffrey E. Hinton
- Jitendra Malik
- Alex Krizhevsky
- Yoshua Bengio
Who trusts Arpit Mittal overall
- Supreeth Narasimhaswamy
- James Thorne
- Aisha Urooj Khan
- Andreas Vlachos
- Xiaolong Zhu
- Dandan Shan
- Yezhou Yang
- Roy Shilkrot
- Sven Bambach
- Zhihan Lv
Papers from Arpit Mittal's perspective
Ordered by how strongly the researchers Arpit Mittal 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- FEVER: a Large-scale Dataset for Fact Extraction and VERification (2018) — 2,295 citations
- Hand detection using multiple proposals (2011) — 292 citations
- The FEVER2.0 Shared Task (2019) — 112 citations
- The Fact Extraction and VERification (FEVER) Shared Task (2018) — 272 citations
- Evaluating adversarial attacks against multiple fact verification systems (2019) — 52 citations
- The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task (2021)
- FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information (2021) — 259 citations