19 citations · 27 across the 7 of their papers we have counts for
12 papers
Noisy Channel for Automatic Text Simplification
Oscar M Cumbicus-Pineda, Iker Gutiérrez-Fandiño, Itziar Gonzalez-Dios +1
In this paper we present a simple re-ranking method for Automatic Sentence Simplification based on the noisy channel scheme. Instead of directly computing the best simplification g…
Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources
Angelina McMillan-Major, Zaid Alyafeai, Stella Biderman +15
In recent years, large-scale data collection efforts have prioritized the amount of data collected in order to improve the modeling capabilities of large language models. This prio…
Inferring spatial relations from textual descriptions of images
Aitzol Elu, Gorka Azkune, Oier Lopez de Lacalle +3
Generating an image from its textual description requires both a certain level of language understanding and common sense knowledge about the spatial relations of the physical enti…
Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning
Jon Ander Campos, Kyunghyun Cho, Arantxa Otegi +3
The interaction of conversational systems with users poses an exciting opportunity for improving them after deployment, but little evidence has been provided of its feasibility. In…
Spot The Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems
Jan Deriu, Don Tuggener, Pius von Däniken +6
The lack of time-efficient and reliable evaluation methods hamper the development of conversational dialogue systems (chatbots). Evaluations requiring humans to converse with chatb…
DoQA -- Accessing Domain-Specific FAQs via Conversational QA
Jon Ander Campos, Arantxa Otegi, Aitor Soroa +3
The goal of this work is to build conversational Question Answering (QA) interfaces for the large body of domain-specific information available in FAQ sites. We present DoQA, a dat…