Kazuma Hashimoto

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 9 papers; trusts 533 researchers and is trusted by 139 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 236 citations into it; #2,256 of 35,345 by trust here, #3,412 by citations
• Natural Language Processing — 188 citations into it; #1,162 of 5,688 by trust here, #1,092 by citations
• Computer Vision and Pattern Recognition — 105 citations into it; #3,523 of 21,575 by trust here, #2,902 by citations
• Model Architectures — 51 citations into it
• Evaluation & Benchmarks — 31 citations into it; #2,588 of 3,147 by trust here, #2,743 by citations
• Representation & Self-Supervised Learning — 30 citations into it
• Information Retrieval & Search — 26 citations into it
• Optimization & Training — 14 citations into it

Whom Kazuma Hashimoto trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoshua Bengio
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Richard Socher
5. Diederik P. Kingma
6. Christopher D. Manning
7. Alex Graves
8. Alex Krizhevsky
9. Kyunghyun Cho
10. Sepp Hochreiter

Who trusts Kazuma Hashimoto overall

1. Caiming Xiong
2. Bryan McCann
3. Richard Socher
4. Grzegorz Chrupała
5. Yoshimasa Tsuruoka
6. Sebastian Ruder
7. Yonatan Belinkov
8. Sewon Min
9. Matthew E. Peters
10. Christopher D. Manning

Papers from Kazuma Hashimoto's perspective

Ordered by how strongly the researchers Kazuma Hashimoto trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks (2016) — 589 citations
• Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering (2019) — 327 citations
• Tree-to-Sequence Attentional Neural Machine Translation (2016) — 279 citations
• Multilingual Extractive Reading Comprehension by Runtime Machine Translation (2018) — 61 citations
• Neural Machine Translation with Source-Side Latent Graph Parsing (2017) — 48 citations
• RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering (2021) — 212 citations
• Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference (2020) — 99 citations
• Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking (2019) — 179 citations
• Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT (2020) — 117 citations