31.774, Calls: Computational Linguistics/USA

[The LINGUIST List]

LINGUIST List: Vol-31-774. Mon Feb 24 2020. ISSN: 1069 - 4875.

Subject: 31.774, Calls: Computational Linguistics/USA

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Date: Mon, 24 Feb 2020 15:46:44
From: Larry Moss [lmoss at indiana.edu]
Subject: Natural Logic Meets Machine Learning

 
Full Title: Natural Logic Meets Machine Learning 
Short Title: NALOMA'20 

Date: 11-Jul-2020 - 17-Jul-2020
Location: Waltham, MA, USA 
Contact Person: Larry Moss
Meeting Email: naloma20 at easychair.org
Web Site: https://typo.uni-konstanz.de/naloma20/ 

Linguistic Field(s): Computational Linguistics 

Subject Language(s): English (eng)

Call Deadline: 15-Apr-2020 

Meeting Description:

NAtural LOgic Meets MAchine Learning (NALOMA) is the first workshop of its
kind, aiming to bridge the gap between Machine Learning and Natural Logic. It
will take place from July 11-July 17, 2020, during the 9th North American
Summer School for Logic, Language, and Information (NASSLLI) at Brandeis
University in Waltham, Massachusetts.

Recent models of Natural Language Inference (NLI) have made considerable
progress in the last couple of years and have achieved performance at nearly
human-level. Even though this last statement might still be an exaggeration,
it is indeed true that NLI models are capable of doing more things than we
thought they would some years ago. On the other hand, research on symbolic
methods for NLI has not been fully abandoned. One such area that is still
flourishing is research on Natural Logic. There is actually renewed interest
in monotonicity inference, and connections with theorem provers and tableau
systems from standard areas of logic.

Within this context, the aim of this workshop is to bring together researchers
working in both Natural Logic and Machine Learning approaches to NLI,
initiating a discussion with the two sets of researchers that have been
largely unconnected up to now.


Call for Papers: 

We invite submissions on topics included but not limited to:
 -  reasoning systems that integrate logic-based methods with neural networks;
 - creation, evaluation, and criticism of NLI datasets;
 - training data augmentation using logic;
 - explainable models of NLI;
 - opening the “black box” of machine learning in NLI;
 - probabilistic semantics in connection with NLI;
 - downstream applications of NLI;
 - comparison and contrast between human-level and machine-level work in NLI;
 - linguistics semantics and contemporary NLI.
 - dialogue systems, QA and information retrieval systems that use (natural)
logic and machine learning.

We accept two types of submission:
 - Archival (long or short) papers should report on complete, original and
unpublished research. Accepted papers will be published in the workshop
proceedings and will appear in the ACL anthology.

 - Extended abstracts may report on work in progress or work that was recently
published/accepted at a different venue. Extended abstracts will not be
included in the workshop proceedings. Thus, the unpublished work will retain
the status and can be submitted to another venue. Extended abstracts will be
linked at the workshop webpage.

Both accepted papers and extended abstracts are expected to be presented at
the workshop. Extended abstracts will be presented as talks or posters if
selected by the program committee.

Authors must submit non-anonymized extended abstracts or papers before April
15. Both extended abstracts and papers must be formatted according to the ACL
style. The extended abstracts should not contain an abstract section and may
consist of up to 2 pages of content, plus unlimited references. Short and long
papers may consist of up to 4 and 8 pages of content, respectively, plus
unlimited references. Camera-ready versions of papers will be given one
additional page of content so that reviewers’ comments can be taken into
account.

Both extended abstracts and follow-up papers should be submitted via EasyChair
at https://easychair.org/conferences/?conf=nlmml20




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