Thomas Scialom

According to our database1, Thomas Scialom authored at least 42 papers between 2019 and 2024.

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Bibliography

2024
GAIA: a benchmark for General AI Assistants.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Nougat: Neural Optical Understanding for Academic Documents.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Augmented Language Models: a Survey.
Trans. Mach. Learn. Res., 2023

WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models.
CoRR, 2023

GAIA: a benchmark for General AI Assistants.
CoRR, 2023

Code Llama: Open Foundation Models for Code.
CoRR, 2023

Llama 2: Open Foundation and Fine-Tuned Chat Models.
CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.
CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Natural Language Generation with Reinforcement Learning. (Génération de Langage Naturel par Apprentissage par Renforcement).
PhD thesis, 2022

Galactica: A Large Language Model for Science.
CoRR, 2022

Continual-T0: Progressively Instructing 50+ Tasks to Language Models Without Forgetting.
CoRR, 2022

Choisir le bon co-équipier pour la génération coopérative de texte (Choosing The Right Teammate For Cooperative Text Generation).
Proceedings of the Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale, 2022

Which Discriminator for Cooperative Text Generation?
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

TRUE: Re-evaluating Factual Consistency Evaluation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Generative Cooperative Networks for Natural Language Generation.
Proceedings of the International Conference on Machine Learning, 2022

Fine-tuned Language Models are Continual Learners.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

A Multifaceted Framework to Evaluate Evasion, Content Preservation, and Misattribution in Authorship Obfuscation Techniques.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation.
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CoRR, 2021

BEAMetrics: A Benchmark for Language Generation Evaluation Evaluation.
CoRR, 2021

Rethinking Automatic Evaluation in Sentence Simplification.
CoRR, 2021

SAFEval: Summarization Asks for Fact-based Evaluation.
CoRR, 2021

To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

QuestEval: Summarization Asks for Fact-based Evaluation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Skim-Attention: Learning to Focus via Document Layout.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

QACE: Asking Questions to Evaluate an Image Caption.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020
BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations.
CoRR, 2020

ColdGANs: Taming Language GANs with Cautious Sampling Strategies.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Project PIAF: Building a Native French Question-Answering Dataset.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

What BERT Sees: Cross-Modal Transfer for Visual Question Generation.
Proceedings of the 13th International Conference on Natural Language Generation, 2020

Discriminative Adversarial Search for Abstractive Summarization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Toward Stance-based Personas for Opinionated Dialogues.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

MLSUM: The Multilingual Summarization Corpus.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Ask to Learn: A Study on Curiosity-driven Question Generation.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
Answers Unite! Unsupervised Metrics for Reinforced Summarization Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Architecture basée sur les mécanismes d'attention: le cas de la génération de questions neuronales.
Proceedings of the COnférence en Recherche d'Informations et Applications, 2019

Self-Attention Architectures for Answer-Agnostic Neural Question Generation.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019


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