[Corpora-List] Second CfP: Workshop on COmmonsense INference in NLP (COIN) @ EMNLP-IJCNLP 2019

Simon Ostermann simono at coli.uni-saarland.de
Fri Jun 14 10:34:18 CEST 2019


Second Call for Papers: COmmonsense INference in NLP (COIN)

Workshop to be held in conjunction with EMNLP-IJCNLP 2019 in Hong Kong

*!! The submission is now open: **https://www.softconf.com/emnlp2019/ws-COIN <https://www.softconf.com/emnlp2019/ws-COIN>*

*!! The evaluation phase for both tasks starts today.*

Website: https://coinnlp.github.io/

## Summary ##

Research in natural language understanding and textual inference has advanced considerably in recent years, resulting in powerful models that are able to read and understand texts, even outperforming humans in some cases. However, it remains challenging to answer questions that go beyond the texts themselves, requiring the use of additional commonsense knowledge.

The COIN workshop aims at bringing together researchers that are interested in modeling commonsense knowledge, developing computational models thereof, and applying commonsense inference methods in NLP tasks. We are interested in any type of commonsense knowledge representation, and explicitly encourage work that makes use of knowledge bases and approaches developed to mine or learn commonsense from other sources. The workshop is also open for evaluation proposals that explore new ways of evaluating methods of commonsense inference, going beyond established natural language processing tasks.

## Submission ##

We invite both long (8 pages) and short (4 page) papers. The limits refer to the content and any number of additional pages for references are allowed. The papers should follow the EMNLP-IJCNLP 2019 formatting instructions (see http://www.emnlp-ijcnlp2019.org/calls/papers#formatting-requirements).

Each submission must be anonymized, written in English, and contain a title and abstract. We especially welcome the following types of papers:

-

Technical papers that demonstrate the impact of commonsense knowledge

inference in tasks and applications

-

Position papers that reflect innovative, creative and thought-provoking

ideas

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Theoretical papers that advance our understanding of commonsense

inference

-

Papers that describe data collection efforts for evaluating commonsense

inference

-

Survey papers that review the current state of research in a specific

area

-

Papers describing submissions to the shared tasks described below

Submission is handled via Softconf: *https://www.softconf.com/emnlp2019/ws-COIN* <https://www.softconf.com/emnlp2019/ws-COIN>

## Shared Tasks ##

The workshop will also include two shared tasks on commonsense machine reading comprehension in English. Task 1 is based on everyday scenarios and uses an extended and updated version of MCScript, as a continuation of the SemEval 2018 shared task 11. Task 2 is based on news events and uses ReCoRD, a large cloze-style dataset that requires commonsense inference. Participants are encouraged to use any external commonsense knowledge resources that could improve their systems. Please consult the workshop website for more details.

## Important Dates ##

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June 14, 2019: Beginning of evaluation phase for the shared tasks

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June 14, 2019: Second call for workshop papers

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July 5, 2019: End of evaluation phase for the shared tasks

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Submission Deadline: August 19

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Notification of acceptance: September 16

-

Camera-ready papers due: September 30

## Organizing Committee ##

Peter Clark, Allen Institute for AI

Simon Ostermann, Saarland University

Michael Roth, University of Stuttgart/Saarland University

Robyn Speer, Luminoso Technologies, Inc.

Sheng Zhang, Johns Hopkins University

## Program Committee ##

Ken Barker, IBM Research

Yonatan Bisk, University of Washington

Nate Chambers, United States Naval Academy

Hans Chalupsky, USC Information Sciences Institute

Vera Demberg, Saarland University

Anette Frank, Heidelberg University

Andrew S. Gordon, University of Southern California

Jonathan Gordon, Vassar College

Jerry Hobbs, USC Information Sciences Institute

Andrew McCallum, University of Massachusetts Amherst

Gerard de Melo, Rutgers University

Elizabeth Merkhofer, MITRE Corporation

Todor Mihaylov, Heidelberg University

Ashutosh Modi, Disney Research

Sreyasi Nag Chowdhury, Max-Planck-Institute for Informatics

Hannah Rashkin, University of Washington

Niket Tandon, Allen Institute for AI

Adam Trischler, Microsoft Research

Bishan Yang, LAER.AI <http://laer.ai/>

Peter Yeh, Nuance Communications, Inc.

-- Simon Ostermann Ph.D. Student | Researcher http://www.coli.uni-saarland.de/~simono/

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