Toufique Ahmed

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 116 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it; #17,376 of 35,345 by trust here, #23,077 by citations
• Natural Language Processing — 57 citations into it; #3,051 of 5,688 by trust here, #4,601 by citations
• Information Systems — 43 citations into it; #3,499 of 8,771 by trust here, #5,078 by citations
• Software — 24 citations into it; #1,169 of 1,227 by trust here, #965 by citations
• Code Generation & Program Synthesis — 19 citations into it; #216 of 220 by trust here, #197 by citations
• Large Language Models — 17 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Signal Processing — 13 citations into it

Whom Toufique Ahmed trusts overall

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

1. Chin-Yew Lin
2. Miltiadis Allamanis
3. Ilya Sutskever
4. Jacob Devlin
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Diederik P. Kingma
8. Oriol Vinyals
9. Rico Sennrich
10. Alex Krizhevsky

Who trusts Toufique Ahmed overall

1. Federico Cassano
2. Kevin Jesse
3. Ming-Ho Yee
4. Prem Devanbu
5. Mingwei Liu
6. Arjun Guha

Papers from Toufique Ahmed's perspective

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

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

Their papers

• Learning type annotation: is big data enough? (2021) — 43 citations
• Few-shot training LLMs for project-specific code-summarization (2022) — 359 citations
• Multilingual training for Software Engineering (2021) — 97 citations