Lambert Mathias

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 82 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 101 citations into it; #25,205 of 35,345 by trust here, #18,586 by citations
• Natural Language Processing — 75 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it; #15,614 of 21,575 by trust here, #15,955 by citations
• Evaluation & Benchmarks — 21 citations into it
• Prompting & Reasoning — 20 citations into it
• Model Architectures — 15 citations into it
• Representation & Self-Supervised Learning — 10 citations into it

Whom Lambert Mathias trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Ilya Sutskever
4. Diederik P. Kingma
5. Kyunghyun Cho
6. Alex Krizhevsky
7. Oriol Vinyals
8. Yann LeCun
9. Richard Socher
10. Kaiming He

Who trusts Lambert Mathias overall

1. Jianpeng Cheng

Papers from Lambert Mathias's perspective

Ordered by how strongly the researchers Lambert Mathias 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
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. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Prompt-free and Efficient Few-shot Learning with Language Models (2022) — 76 citations
• Transfer Learning for Neural Semantic Parsing (2017) — 65 citations
• Policy Compliance Detection via Expression Tree Inference (2022)
• UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning (2021) — 235 citations