Sean MacAvaney
Artificial Intelligence · 2017–2021
A researcher in the Science corpus: 11 papers; trusts 156 researchers and is trusted by 33 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 178 citations into it; #5,968 of 35,345 by trust here, #7,413 by citations
- Natural Language Processing — 86 citations into it; #1,758 of 5,688 by trust here, #2,307 by citations
- Information Retrieval & Search — 83 citations into it; #192 of 1,022 by trust here, #284 by citations
- Information Systems — 68 citations into it; #5,229 of 8,771 by trust here, #2,406 by citations
- Computer Vision and Pattern Recognition — 41 citations into it
- Large Language Models — 29 citations into it
- Representation & Self-Supervised Learning — 16 citations into it
- Model Architectures — 11 citations into it
Whom Sean MacAvaney trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Jacob Devlin
- Rodrigo Nogueira
- Zhuyun Dai
- Yoshua Bengio
- Geoffrey E. Hinton
- Jimmy J. Lin
- Peilin Yang
- Andrew Yates
- Kyunghyun Cho
Who trusts Sean MacAvaney overall
- Rodrigo Nogueira
- Sebastian Hofstätter
- Jimmy J. Lin
- Zeynep Akkalyoncu Yilmaz
- Zhuyun Dai
- Wei Yang
- Kaitao Zhang
- Zhenghao Liu
- Luca Soldaini
- Chenyan Xiong
Papers from Sean MacAvaney's perspective
Ordered by how strongly the researchers Sean MacAvaney 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- CEDR: Contextualized Embeddings for Document Ranking (2019) — 371 citations
- SLEDGE: A Simple Yet Effective Baseline for Coronavirus Scientific Knowledge Search (2020) — 23 citations
- Efficient Document Re-Ranking for Transformers by Precomputing Term Representations (2020) — 132 citations
- Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task (2021) — 35 citations
- ToxCCIn: Toxic Content Classification with Interpretability (2021) — 20 citations
- Expansion via Prediction of Importance with Contextualization (2020) — 122 citations
- Training Curricula for Open Domain Answer Re-Ranking (2020) — 20 citations
- Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-Shot Learning (2019) — 31 citations
- Hate speech detection: Challenges and solutions (2019) — 568 citations
- Contextualized PACRR for Complex Answer Retrieval (2017) — 9 citations
- Content-Based Weak Supervision for Ad-Hoc Re-Ranking (2017) — 46 citations