1st Workshop on Evaluating NLG Evaluation, collocated with INLG

EvalNLGEval 2020

Artificial Intelligence

Workshop overview:
This workshop is intended as a discussion platform on the status and the future of the evaluation of Natural Language Generation systems. Among other topics, we will discuss current evaluation quality, human versus automated metrics, and the development of shared tasks for NLG evaluation. The workshop also involves an ‘unshared task’, where participants are invited to experiment with evaluation data from earlier shared tasks.
Important dates:
Call for workshop papers or abstracts - July 20, 2020
Submissions due - September 20, 2020
Notification of acceptance - October 20, 2020
Camera ready papers due - November 20, 2020
Workshop: December 18, 2020
We encourage a range of papers ranging from commentary and meta-evaluation of existing evaluation strategies to the suggestion of new metrics. We specifically place emphasis on the methodology and linguistic aspects of evaluation. We invite papers on any topic related to the evaluation of NLG systems, including (but not limited to):
Qualitative studies, definitions of evaluation metrics (e.g., readability, fluency, semantic correctness)
Crowdsourcing Strategies, qualitative tests for crowdsourcing (How to elucidate evaluation metrics?)
Looking at individual differences and cognitive biases in human evaluation (expert vs. non-expert, L1 vs L2 speakers)
Best practices for system evaluations (How does your lab choose models?)
Qualitative study/error analysis approaches
Demo: Systems that make the evaluation easier
Comparison of metrics across different NLG tasks (captioning, data2text, story generation, summarization…) or different languages (with a focus on low-resource languages)
Evaluation surveys
Position papers and commentary on trends in evaluation
We encourage the submission of “task proposals”, where authors can propose shared tasks for next year’s edition of the workshop.
Unshared Task:
This year’s edition also features an unshared task: rather than working towards a specific goal, we encourage participants to use a specific collection of datasets, for any evaluation-related goal. For example: comparing a new evaluation method with existing ratings, or carrying out a subset analysis. This allows us to put the results from previous shared tasks in perspective, and helps us develop better evaluation metrics for future shared tasks. Working on the same datasets allows for more focused discussions at the workshop.
Datasets for this year’s edition are existing datasets with system outputs and human ratings. Participants may use any of these for their unshared task submission:
E2E NLG Challenge (http://www.macs.hw.ac.uk/InteractionLab/E2E/)
WebNLG Challenge 2017 (https://webnlg-challenge.loria.fr/challenge_2017/)
Surface Realization Shared Task (SRST) 2019 (http://taln.upf.edu/pages/msr2019-ws/SRST.html)
Submission Formats:
Archival papers (up to 8 pages excluding references; shorter submissions are also welcome)
Non-archival abstract of papers within the topic accepted somewhere else or under submission at the main INLG 2020 (1-2 pages)
Demo papers (1-2 pages)
Shubham Agarwal
Ondrej Dusek
Sebastian Gehrmann
Dimitra Gkatzia
Ioannis Konstas
Emiel van Miltenburg
Sashank Santhanam
Samira Shaikh
Contact: evalnlg.inlg@gmail.com