Akiko Aizawa
Artificial Intelligence · 2003–2021
A researcher in the Science corpus: 7 papers; trusts 366 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 135 citations into it; #6,301 of 35,345 by trust here, #7,606 by citations
- Natural Language Processing — 127 citations into it; #1,923 of 5,688 by trust here, #1,939 by citations
- Evaluation & Benchmarks — 65 citations into it; #1,523 of 3,147 by trust here, #1,683 by citations
- Computer Vision and Pattern Recognition — 61 citations into it; #8,353 of 21,575 by trust here, #7,092 by citations
- Information Retrieval & Search — 15 citations into it
- Multimodal Learning — 14 citations into it
- Information Systems — 10 citations into it; #1,782 of 8,771 by trust here, #4,682 by citations
- Large Language Models — 9 citations into it
Whom Akiko Aizawa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Andrew McCallum
- Geoffrey E. Hinton
- Yoshua Bengio
- W. Bruce Croft
- Diederik P. Kingma
- Kenneth Ward Church
- Ilya Sutskever
- Kaiming He
- Alex Krizhevsky
Who trusts Akiko Aizawa overall
- Alessandro Vinciarelli
- Masumi Shirakawa
- Stephen E. Robertson
- Takahiro Hara
- Ho Chung Wu
- Shojiro Nishio
- Emma Kerinec
- Rasmus Elsborg Madsen
- Harsh Trivedi
- D. Angelov
Papers from Akiko Aizawa's perspective
Ordered by how strongly the researchers Akiko Aizawa 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- What Makes Reading Comprehension Questions Easier? (2018) — 127 citations
- Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets (2019) — 92 citations
- Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps (2020) — 1,443 citations
- Prerequisite Skills for Reading Comprehension: Multi-Perspective Analysis of MCTest Datasets and Systems (2017) — 21 citations
- Effect of Vision-and-Language Extensions on Natural Language Understanding in Vision-and-Language Models (2021) — 6 citations
- Keyphrase Generation for Scientific Document Retrieval (2020) — 48 citations
- An information-theoretic perspective of tf-idf measures (2003) — 1,384 citations