Thomas Scialom

To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs

2021 · arXiv (Cornell University)

Due to the discrete nature of words, language GANs require to be optimized from rewards provided by discriminator networks, via reinforcement learning methods. This is a much harder setting than for continuous tasks, which enjoy …

NL-Augmenter 🦎 → 🐍 A Framework for Task-Sensitive Natural Language Augmentation

2023 · Northern European Journal of Language Technology

Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural …

TRUE: Re-evaluating Factual Consistency Evaluation

2022 · arXiv (Cornell University)

Grounded text generation systems often generate text that contains factual inconsistencies, hindering their real-world applicability. Automatic factual consistency evaluation may help alleviate this limitation by accelerating evaluation cycles, filtering inconsistent outputs and augmenting training data. …

Answers Unite! Unsupervised Metrics for Reinforced Summarization Models

2019

Thomas Scialom, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Llama 2: Open Foundation and Fine-Tuned Chat Models

2023 · arXiv (Cornell University)

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2-Chat, …