*Apologies for cross-posting*

Fifth Workshop on Gender Bias in Natural Language Processing

Bangkok, Thailand, on August 16, 2024

https://genderbiasnlp.talp.cat/ Final Call for Papers and Updated Dates

Gender bias, among other demographic biases (e.g. race, nationality, religion), in machine-learned models is of increasing interest to the scientific community and industry. Models of natural language are highly affected by such biases, which are present in widely used products and can lead to poor user experiences. There is a growing body of research into improved representations of gender in NLP models. Key example approaches are to build and use balanced training and evaluation datasets (e.g. Webster et al., 2018), and to change the learning algorithms themselves (e.g. Bolukbasi et al., 2016). While these approaches show promising results, there is more to do to solve identified and future bias issues. In order to make progress as a field, we need to create widespread awareness of bias and a consensus on how to work against it, for instance by developing standard tasks and metrics. Our workshop provides a forum to achieve this goal. Topics of interest We invite submissions of technical work exploring the detection, measurement, and mediation of gender bias in NLP models and applications. Other important topics are the creation of datasets, identifying and assessing relevant biases or focusing on fairness in NLP systems. Finally, the workshop is also open to non-technical work addressing sociological perspectives, and we strongly encourage critical reflections on the sources and implications of bias throughout all types of work. In addition this year we are organising a Shared Task on Gender Bias Machine Translation evaluation. Paper Submission Information Submissions will be accepted as short papers (4-6 pages) and as long papers (8-10 pages), plus additional pages for references, following the ACL 2024 guidelines. Supplementary material can be added, but should not be central to the argument of the paper. Blind submission is required. Each paper should include a statement which explicitly defines (a) what system behaviors are considered as bias in the work and (b) why those behaviors are harmful, in what ways, and to whom (cf. Blodgett et al. (2020)). More information on this requirement, which was successfully introduced at GeBNLP 2020, can be found on the workshop website. We also encourage authors to engage with definitions of bias and other relevant concepts such as prejudice, harm, discrimination from outside NLP, especially from social sciences and normative ethics, in this statement and in their work in general.

Non-archival option The authors have the option of submitting research as non-archival, meaning that the paper will not be published in the conference proceedings. We expect these submissions to describe the same quality of work and format as archival submissions. Updated dates: May 24, 2024: Workshop Paper Due Date June 21, 2024: Notification of Acceptance July 5, 2024: Camera-ready papers due August 16, 2024: Workshop Dates Keynote Speakers. Isabelle Augenstein, University of Copenhagen Hal Daumé III, University of Maryland and Microsoft Research NYC

Organizers. Christine Basta, Alexandria University Marta R. Costa-jussà, FAIR, Meta, Agnieszka Falénska, University of Stuttgart Seraphina Goldfarb-Tarrant, Cohere Debora Nozza, Bocconi University