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NaLoMa 2020: Natural Logic meets Machine Learning, Waltham MA (U.S.A.)
NATURAL LOGIC MEETS MACHINE LEARNING (NALOMA'2020)
Workshop at NASSLLI 2020
July 11-17, 2020
Brandeis University, Waltham MA USA
URL: https://typo.uni-konstanz.de/naloma20/
AIMS
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unpublished research.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
INVITED SPEAKERS
Lauri Karttunen, Stanford University
Ellie Pavlick, Brown University
Mark Steedman, University of Edinburgh
IMPORTANT DATES
Submission of papers & extended abstracts: April 15
Notification: May 1
Final versions due: June 1
Workshop: July 11-17
PROGRAM COMMITTEE
Lawrence S. Moss (Chair), Indiana University
Lasha Abziniadize, University of Groningen
Stergios Chatzikyriakidis, University of Gothenburg
Hai Hu, Indiana University
Thomas Icard, Stanford University
Aikaterini-Lida Kalouli, University of Konstanz
Hitomi Yanaka, Riken
CONTACT: naloma20@easychair.org
URL: https://typo.uni-konstanz.de/naloma20/
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