Yada Pruksachatkun
Artificial Intelligence · 2019–2024
A researcher in the Science corpus: 8 papers; trusts 145 researchers and is trusted by 60 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 362 citations into it; #4,209 of 35,345 by trust here, #1,654 by citations
- Natural Language Processing — 285 citations into it; #5,218 of 5,688 by trust here, #1,992 by citations
- Evaluation & Benchmarks — 116 citations into it; #981 of 3,147 by trust here, #267 by citations
- Large Language Models — 92 citations into it; #223 of 799 by trust here, #139 by citations
- Computer Vision and Pattern Recognition — 91 citations into it; #5,814 of 21,575 by trust here, #1,484 by citations
- Representation & Self-Supervised Learning — 35 citations into it
- General Social Sciences — 18 citations into it
- Optimization & Training — 9 citations into it
Whom Yada Pruksachatkun trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Richard Socher
- Ilya Sutskever
- Christopher D. Manning
- Alec Radford
- Alex Krizhevsky
- Jacob Devlin
- Jimmy Ba
Who trusts Yada Pruksachatkun overall
- Samuel R. Bowman
- Clara Vania
- Yi Tay
- Timo Schick
- Tu Vu
- Alex Warstadt
- Daniel Khashabi
- Mostafa Dehghani
- Victor Sanh
- Noam Shazeer
Papers from Yada Pruksachatkun's perspective
Ordered by how strongly the researchers Yada Pruksachatkun trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- 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
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems (2019) — 2,854 citations
- Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? (2020) — 210 citations
- BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation (2021) — 594 citations
- jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models (2020) — 97 citations
- English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too (2020) — 69 citations
- On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations (2022) — 112 citations
- When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards (2024) — 153 citations
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations