[Corpora-List] HumEval Workshop on Human Evaluation of NLP Systems at EACL'21: Call for Participation

a belz a.s.belz at gmail.com
Wed Apr 7 16:28:38 CEST 2021

====================================================== HumEval Workshop on Human Evaluation of NLP Systems at EACL'21 19 April 2021 Online from Kyiv, Ukraine https://humeval.github.io/ ======================================================


Early registration ends: 7 April 2021

Invited Speakers: Margaret Mitchell and Lucia Specia

Open-mic session: For information regarding how to participate in this open discussion session please see in programme below.

Programme <https://humeval.github.io/programme/>



Chair: Anya Belz


Invited Talk: Disagreement in Human Evaluation: Blame the Task not the Annotators

by Lucia Specia <https://www.imperial.ac.uk/people/l.specia>, Imperial College London and University of Sheffield

It is well known that human evaluators are prone to disagreement and that this is a problem for reliability and reproducibility of evaluation experiments. The reasons for disagreement can fall into two broad categories: (1) human evaluator, including under-trained, under-incentivised, lacking expertise, or ill-intended individuals, e.g., cheaters; and (2) task, including ill-definition, poor guidelines, suboptimal setup, or inherent subjectivity. While in an ideal evaluation experiment many of these elements will be controlled for, I argue that task subjectivity is a much harder issue. In this talk I will cover a number of evaluation experiments on tasks with variable degrees of subjectivity, discuss their levels of disagreement along with other issues, and cover a few practical approaches do address them. I hope this will lead to an open discussion on possible strategies and directions to alleviate this problem.


Oral Session 1 (NLG)


It’s Commonsense, isn’t it? Demystifying Human Evaluations in Commonsense-Enhanced NLG systems

Miruna-Adriana Clinciu, Dimitra Gkatzia and Saad Mahamood


Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation

Jakob Nyberg, Maike Paetzel and Ramesh Manuvinakurike


Trading Off Diversity and Quality in Natural Language Generation

Hugh Zhang, Daniel Duckworth, Daphne Ippolito and Arvind Neelakantan




Oral Session 2 (MT)


Towards Document-Level Human MT Evaluation: On the Issues of Annotator Agreement, Effort and Misevaluation

Sheila Castilho


Is This Translation Error Critical?: Classification-Based Human and Automatic Machine Translation Evaluation Focusing on Critical Errors

Katsuhito Sudoh, Kosuke Takahashi and Satoshi Nakamura


Poster Session

- Towards Objectively Evaluating the Quality of Generated Medical Summaries

Francesco Moramarco, Damir Juric, Aleksandar Savkov and Ehud Reiter

- A Preliminary Study on Evaluating Consultation Notes With Post-Editing

Francesco Moramarco, Alex Papadopoulos Korfiatis, Aleksandar Savkov and Ehud Reiter

- The Great Misalignment Problem in Human Evaluation of NLP Methods

Mika Hämäläinen and Khalid Alnajjar

- A View From the Crowd: Evaluation Challenges for Time-Offset Interaction Applications

Alberto Chierici and Nizar Habash

- Reliability of Human Evaluation for Text Summarization: Lessons Learned and Challenges Ahead

Neslihan Iskender, Tim Polzehl and Sebastian Möller

- On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs

Roman Grundkiewicz, Marcin Junczys-Dowmunt, Christian Federmann and Tom Kocmi

- Eliciting Explicit Knowledge From Domain Experts in Direct Intrinsic Evaluation of Word Embeddings for Specialized Domains

Goya van Boven and Jelke Bloem

- Detecting Post-Edited References and Their Effect on Human Evaluation

Věra Kloudová, Ondřej Bojar and Martin Popel




Oral Session 3


A Case Study of Efficacy and Challenges in Practical Human-in-Loop Evaluation of NLP Systems Using Checklist

Shaily Bhatt, Rahul Jain, Sandipan Dandapat and Sunayana Sitaram


Interrater Disagreement Resolution: A Systematic Procedure to Reach Consensus in Annotation Tasks

Yvette Oortwijn, Thijs Ossenkoppele and Arianna Betti


Open-Mic Discussion Panel

Chair: Ehud Reiter

Discussion session will be open to all participants. Anyone who is interested in speaking for 3 mins about any topic relevant to the workshop should email Ehud Reiter (e.reiter at abdn.ac.uk). We will follow these short presentations by a general discussion.




Invited Talk: The Ins and Outs of Ethics-Informed Evaluation

by Margaret Mitchell <http://www.m-mitchell.com/>

The modern train/test paradigm in Artificial Intelligence (AI) and Machine Learning (ML) narrows what we can understand about AI models, and skews our understanding of models’ robustness in different environments. In this talk, I will work through the different factors involved in ethics-informed AI evaluation, including connections to ML training and ML fairness, and present an overarching evaluation protocol that addresses a multitude of considerations in developing ethical AI.


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