*Last Call for Papers*: The sixth edition of BlackboxNLP, co-located with EMNLP 2023, in Singapore.

*Important dates*

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****September 1, 2023 – Submission deadline *(via Softconf: https://www.softconf.com/emnlp2023/blackboxnlp2023/)***

October 6, 2023 – Notification of acceptance

October 18, 2023 – Camera-ready papers due

December 7, 2023 – Workshop

Note: All deadlines are *11:59 PM UTC-12 (anywhere on Earth)*.

*Workshop description:*

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Many recent performance improvements in NLP have come at the cost of understanding of the systems. How do we assess what representations and computations models learn? How do we formalize desirable properties of interpretable models, and measure the extent to which existing models achieve them? How can we build models that better encode these properties? What can new or existing tools tell us about these systems’ inductive biases?

The goal of this workshop is to bring together researchers focused on interpreting and explaining NLP models by taking inspiration from fields such as machine learning, psychology, linguistics, and neuroscience. We hope the workshop will serve as an interdisciplinary meetup that allows for cross-collaboration.

Topics of interest include, but are not limited to:

* Applying analysis techniques from neuroscience to analyze high-dimensional vector representations in artificial neural networks;

* Analyzing the network’s response to strategically chosen input in order to infer the linguistic generalizations that the network has acquired;

* Examining network performance on simplified or formal languages;

* Mechanistic interpretability, reverse engineering approaches to understanding particular properties of neural models;

* Proposing modifications to neural architectures that increase their interpretability;

* Testing whether interpretable information can be decoded from intermediate representations;

* Explaining specific model predictions made by neural networks;

* Generating and evaluating the quality of adversarial examples in NLP;

* Developing open-source tools for analyzing neural networks in NLP;

* Evaluating the analysis results: how do we know that the analysis is valid?

*Submissions*

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We call for two types of papers:

1) Archival papers. These are papers reporting on completed, original and unpublished research, with a maximum length of 8 pages + references. Papers shorter than this maximum are also welcome. Accepted papers are expected to be presented at the workshop and will be published in the workshop proceedings. They should report on obtained results rather than intended work. These papers will undergo double-blind peer-review, and should thus be anonymized.

2) Extended abstracts. These may report on work in progress or may be cross submissions that have already appeared in a non-NLP venue. The extended abstracts are of maximum 2 pages + references. These submissions are non-archival in order to allow submission to another venue. The selection will not be based on a double-blind review and thus submissions of this type need not be anonymized.

Submissions should follow the official EMNLP 2023 style guidelines.

*The submission site is:* https://www.softconf.com/emnlp2023/blackboxnlp2023/

*Organizers*

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Yonatan Belinkov, Technion

Najoung Kim, Boston University

Sophie Hao, New York University

Arya McCarthy, Johns Hopkins University

Jaap Jumelet, University of Amsterdam

Hosein Mohebbi, Tilburg University

*Contact*

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Please contact the organizers at blackboxnlp@googlegroups.com for any questions.

Read more:

https://blackboxnlp.github.io

https://www.aclweb.org/portal/content/blackboxnlp-2023-6th-workshop-analysin...