ReproHum: Investigating Reproducibility of Human Evaluations in Natural Language Processing

Lead Research Organisation: University of Aberdeen
Department Name: Computing Science


Over the past few months, we have laid the groundwork for the ReproHum project (summarised in the 'pre-project' column in the Work Plan document) with (i) a study of 20 years of human evaluation in NLG which reviewed and labelled 171 papers in detail, (ii) the development of a classification system for NLP evaluations, (iii) a proposal for a shared task for reproducibility of human evaluation in NLG, and (iv) a proposal for a workshop on human evaluation in NLP. We have built an international network of 20 research teams currently working on human evaluation who will actively contribute to this project (see Track Record section), making combined contributions in kind of over £80,000. This pre-project activity has created an advantageous starting position for the proposed work, and means we can 'hit the ground running' with the scientifically interesting core of the work.

In this foundational project, our key goals are the development of a methodological framework for testing the reproducibility of human evaluations in NLP, and of a multi-lab paradigm for carrying out such tests in practice, carrying out the first study of this kind in NLP. We will (i) systematically diagnose the extent of the human evaluation reproducibility problem in NLP and survey related current work to address it (WP1); (ii) develop the theoretical and methodological underpinnings for reproducibility testing in NLP (WP2); (iii) test the suitability of the shared-task paradigm (uniformly popular across NLP fields) for reproducibility testing (WP3); (iv) create a design for multi-test reproducibility studies, and run the ReproHum study, an international large-scale multi-lab effort conducting 50+ individual, coordinated reproduction attempts on human evaluations in NLP from the past 10 years (WP4); and (v) nurture and build international consensus regarding how to address the reproducibility crisis, via technical meetings and growing our international network of researchers (WP5).


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