[Corpora-List] First Call for Papers: ACL-IJCNLP2021 Workshop on "Interactive Learning for Natural Language Processing (InterNLP 2021)"

Ji-Ung Lee lee at ukp.informatik.tu-darmstadt.de
Wed Dec 23 18:36:25 CET 2020


Apologies for cross-postings ------------------------------------------------------ Call for Papers

Workshop on "Interactive Learning for Natural Language Processing (InterNLP 2021)"

Co-located with ACL-IJCNLP 2021 to be held in Bangkok, on August 5-6, 2021

Webpage: https://sites.google.com/view/internlp2021

Important Dates

•First Call for Workshop Papers: December 21, 2020 •Second Call for Workshop Papers: February 15, 2021 •Submission deadline: April 26, 2021 •Notification of acceptance: May 28, 2021 •Camera-ready papers due: June 7, 2021 •Workshop: August 5 or 6, 2021

All deadlines are 11.59 pm UTC -12h (anywhere on Earth).

-------------------------------------------------------- Motivation

As the impact of machine learning on all aspects of our lives continues to grow, the need for systems that learn through interaction with users and the world becomes more and more pressing. Unfortunately, much of the recent success of NLP relies on large datasets and extensive compute re-sources to train and fine-tune models, which then remain fixed. This leaves a research gap for systems that adapt to the changing needs of individual users or allow users to continually correct errors as they emerge. Learning from user interaction is crucial for tasks that require a high grade of personalization and for rapidly changing or complex, multi-step tasks where collecting and annotating large datasets is not feasible, but an informed user can provide guidance.

Topics of Interest

We define Interactive Learning for NLP as training, fine-tuning or otherwise adapting an NLP model to inputs from a human user or teacher. Relevant approaches range from active learning with a human in the loop, to training with implicit user feedback (e.g. clicks), dialogue systems that adapt to user utterances, and training with new forms of human input. Interactive learning is the converse of passive learning from datasets collected offline with no human input during the training process.

We encourage submissions in the following topics, including but not limited to:

•Interactive machine learning methods, theory and practice: from active learning with a user to methods that extract, interpret and aggregate user feedback or preferences from complex interactions, such as natural language instructions.

•User effort: the amount of user effort required for different types of feedback and how users cope with the system misinterpreting instructions.

•Different kinds of user feedback: beyond providing training labels, users may influence and interrogate NLP models in different ways, such as providing natural language instructions or implicit feedback through mouse clicks.

•Evaluation methods: approaches to assessing interactive methods, such as low-effort, easily reproducible methods with real-world users and simulated user models for automated evaluation.

•Reproducibility: procedures for documenting user evaluations and ensuring they are reproducible.

•Data: novel datasets for training and evaluating interactive models.

•Empirical results that investigate scenarios where interactive learning is effective.

Submissions

Submission is electronic, using the Softconf START conference management system. Submission link: to be made available shortly.

Both long and short papers must follow the ACL 2021 style file: https://2021.aclweb.org/calls/papers/#paper-submission-and-templates

We solicit three categories of papers:

•Standard workshop papers: anonymized submissions describing substantially original research not previously published in other venues.

•Extended abstracts: anonymized submissions describing preliminary but interesting ideas or results not previously published in other venues.

•Cross-submissions: non-anonymized papers on relevant topics that have previously been accepted for publication in another venue.

Only standard workshop papers will be included in the proceedings as archival publications. All three categories of papers may be long (maximum 8 pages plus references) or short (maximum 4 pages plus references).

Supplementary Material:

Each submission can be accompanied by a single PDF appendix. The paper submissions need to remain fully self-contained, as these supplementary materials are completely optional, and reviewers are not even asked to review or download them. Supplementary materials need to be fully anonymized to preserve the double-blind reviewing policy.

Dual Submission with ACL is allowed. You will be asked to specify the cross-submission information in the START system. If the paper is accepted to both ACL and the workshop, it will be considered as a cross-submission and will not be a part of the workshop proceedings. If it gets rejected from ACL and accepted to the workshop and you want us to consider it as a standard workshop paper which will be included in the proceedings, please contact us to let us know.

Invited Speakers and Panellists

Speakers in alphabetical order: •Yoav Artzi, Cornell University and ASAPP, Inc. •Dan Goldwasser, Purdue University •Percy Liang, Stanford University •Dan Roth, University of Pennsylvania •Dorsa Sadigh, Stanford University

Panellists in alphabetical order: •Tania Bedrax-Weiss, Google •Ido Dagan, Bar-Ilan University •Dilek Hakkani-Tur, Amazon Alexa AI •Seung-won Hwang, Yonsei University •Julia Kreutzer, Google Research •Alison Smith-Renner, University of Maryland •Yu Zhou, University of California, Davis

The workshop is scheduled to last for one day either August 5th or 6th. If you have any questions, contact us at internlp2021 at googlegroups.com

Workshop organizers

•Kianté Brantley, University of Maryland College Park •Soham Dan, University of Pennsylvania •Iryna Gurevych, Technische Universität Darmstadt •Ji-Ung Lee, Technische Universität Darmstadt •Filip Radlinski, Google •Hinrich Schütze, Ludwig Maximilians Universität Munich •Edwin Simpson, University of Bristol •Lili Yu, ASAPP, Inc. -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 7358 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20201223/9c140e50/attachment.txt>



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