Avirup Sil
Artificial Intelligence · 2013–2024
A researcher in the Science corpus: 10 papers; trusts 200 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 205 citations into it; #10,500 of 35,345 by trust here, #8,439 by citations
- Natural Language Processing — 138 citations into it; #5,492 of 5,688 by trust here, #3,897 by citations
- Computer Vision and Pattern Recognition — 92 citations into it; #20,930 of 21,575 by trust here, #8,021 by citations
- Information Retrieval & Search — 31 citations into it
- Representation & Self-Supervised Learning — 25 citations into it
- Model Architectures — 15 citations into it
- General Social Sciences — 7 citations into it
- Information Systems — 7 citations into it
Whom Avirup Sil trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Richard Socher
- Lev-Arie Ratinov
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Sepp Hochreiter
- Diederik P. Kingma
- Peter D. Turney
- Christopher D. Manning
Who trusts Avirup Sil overall
- Xiao Ling
- Hongwei Wang
- Ying Lin
- Gang Luo
- Ander Barrena
- Hamed Shahbazi
- Sameer Singh
- Fuzheng Zhang
- Heng Ji
- Gourab Kundu
Papers from Avirup Sil's perspective
Ordered by how strongly the researchers Avirup Sil trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Frustratingly Easy Natural Question Answering (2019) — 14 citations
- Re-ranking for joint named-entity recognition and linking (2013) — 134 citations
- MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding (2021) — 37 citations
- Neural Cross-Lingual Entity Linking (2017) — 105 citations
- Span Selection Pre-training for Question Answering (2019) — 76 citations
- Towards Robust Neural Retrieval Models with Synthetic Pre-Training (2021) — 15 citations
- FIRST: Faster Improved Listwise Reranking with Single Token Decoding (2024)
- Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection (2023) — 2,215 citations
- Multi-Stage Pretraining for Low-Resource Domain Adaptation (2020) — 48 citations
- Toward Mention Detection Robustness with Recurrent Neural Networks (2016) — 38 citations