Feb. 13, 2024, 5:48 a.m. | Guanyi Chen Fahime Same Kees van Deemter

cs.CL updates on arXiv.org arxiv.org

Recently, a human evaluation study of Referring Expression Generation (REG) models had an unexpected conclusion: on \textsc{webnlg}, Referring Expressions (REs) generated by the state-of-the-art neural models were not only indistinguishable from the REs in \textsc{webnlg} but also from the REs generated by a simple rule-based system. Here, we argue that this limitation could stem from the use of a purely ratings-based human evaluation (which is a common practice in Natural Language Generation). To investigate these issues, we propose an intrinsic …

art cs.cl evaluation generated human intrinsic simple state study

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

HPC Engineer (x/f/m) - DACH

@ Meshcapade GmbH | Remote, Germany

Director of Machine Learning

@ Axelera AI | Hybrid/Remote - Europe (incl. UK)

Senior Data Scientist - Trendyol Milla

@ Trendyol | Istanbul (All)

Data Scientist, Mid

@ Booz Allen Hamilton | USA, CA, San Diego (1615 Murray Canyon Rd)

Systems Development Engineer , Amazon Robotics Business Applications and Solutions Engineering

@ Amazon.com | Boston, Massachusetts, USA