25 citations · 51 across the 3 of their papers we have counts for
6 papers
TRUE: Re-evaluating Factual Consistency Evaluation
Or Honovich, Roee Aharoni, Jonathan Herzig +7
Grounded text generation systems often generate text that contains factual inconsistencies, hindering their real-world applicability. Automatic factual consistency evaluation may h…
Skim-Attention: Learning to Focus via Document Layout
Laura Nguyen, Thomas Scialom, Jacopo Staiano +1
Transformer-based pre-training techniques of text and layout have proven effective in a number of document understanding tasks. Despite this success, multimodal pre-training models…
QACE: Asking Questions to Evaluate an Image Caption
Hwanhee Lee, Thomas Scialom, Seunghyun Yoon +2
In this paper, we propose QACE, a new metric based on Question Answering for Caption Evaluation. QACE generates questions on the evaluated caption and checks its content by asking…
Rethinking Automatic Evaluation in Sentence Simplification
Thomas Scialom, Louis Martin, Jacopo Staiano +2
Automatic evaluation remains an open research question in Natural Language Generation. In the context of Sentence Simplification, this is particularly challenging: the task require…
QuestEval: Summarization Asks for Fact-based Evaluation
Thomas Scialom, Paul-Alexis Dray, Patrick Gallinari +4
Summarization evaluation remains an open research problem: current metrics such as ROUGE are known to be limited and to correlate poorly with human judgments. To alleviate this iss…
Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
Clément Rebuffel, Thomas Scialom, Laure Soulier +5
QuestEval is a reference-less metric used in text-to-text tasks, that compares the generated summaries directly to the source text, by automatically asking and answering questions.…