Thomas Scialom
Artificial Intelligence · 2019–2024
A researcher in the Science corpus: 22 papers; trusts 912 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 1,030 citations into it; #8,987 of 35,345 by trust here, #895 by citations
- Natural Language Processing — 716 citations into it; #1,854 of 5,688 by trust here, #757 by citations
- Computer Vision and Pattern Recognition — 351 citations into it
- Evaluation & Benchmarks — 316 citations into it
- Large Language Models — 272 citations into it; #577 of 799 by trust here, #88 by citations
- Prompting & Reasoning — 105 citations into it
- Information Systems — 97 citations into it
- Model Architectures — 69 citations into it
Whom Thomas Scialom trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Chin-Yew Lin
- Diederik P. Kingma
- Ronald J. Williams
- Alex Krizhevsky
- Kaiming He
- Richard Socher
- Oriol Vinyals
Who trusts Thomas Scialom overall
- Sebastian Gehrmann
- Philippe Laban
- Rowan Zellers
- Alex Wang
- Zixuan Ke
- Or Honovich
- Elizabeth Clark
- Shuyang Cao
- Alexander R. Fabbri
- Yi-Ting Yeh
Papers from Thomas Scialom's perspective
Ordered by how strongly the researchers Thomas Scialom 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- Llama 2: Open Foundation and Fine-Tuned Chat Models (2023) — 17,670 citations
- Toolformer: Language Models Can Teach Themselves to Use Tools (2023) — 4,753 citations
- MLSUM: The Multilingual Summarization Corpus (2020) — 213 citations
- Answers Unite! Unsupervised Metrics for Reinforced Summarization Models (2019) — 162 citations
- Galactica: A Large Language Model for Science (2022) — 1,065 citations
- Code Llama: Open Foundation Models for Code (2023) — 3,394 citations
- TRUE: Re-evaluating Factual Consistency Evaluation (2022) — 372 citations
- ColdGANs: Taming Language GANs with Cautious Sampling Strategies (2020) — 18 citations
- QuestEval: Summarization Asks for Fact-based Evaluation (2021) — 371 citations
- Augmented Language Models: a Survey (2023) — 579 citations
- Continual-T0: Progressively Instructing 50+ Tasks to Language Models Without Forgetting (2022) — 22 citations
- What BERT Sees: Cross-Modal Transfer for Visual Question Generation (2020) — 14 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering (2020) — 62 citations
- GAIA: a benchmark for General AI Assistants (2023) — 1,001 citations
- Fine-tuned Language Models are Continual Learners (2022) — 185 citations
- Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation (2021) — 38 citations
- The Llama 3 Herd of Models (2024) — 17,085 citations
- Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor (2022) — 487 citations
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations