no code implementations • EMNLP 2020 • Irshad Bhat, Talita Anthonio, Michael Roth
wikiHow is a resource of how-to guidesthat describe the steps necessary to accomplish a goal.
no code implementations • ACL (unimplicit) 2021 • Michael Roth, Talita Anthonio
This paper describes the data, task setup, and results of the shared task at the First Workshop on Understanding Implicit and Underspecified Language (UnImplicit).
no code implementations • LREC 2022 • Talita Anthonio, Anna Sauer, Michael Roth
In this paper, we present a data set of such phrases in English from instructional texts together with multiple possible clarifications.
no code implementations • COLING (CRAC) 2020 • Tatiana Anikina, Alexander Koller, Michael Roth
This work addresses coreference resolution in Abstract Meaning Representation (AMR) graphs, a popular formalism for semantic parsing.
no code implementations • CODI 2021 • Talita Anthonio, Michael Roth
The usage of (co-)referring expressions in discourse contributes to the coherence of a text.
no code implementations • EACL 2021 • Alok Debnath, Michael Roth
WikiHow is an open-domain repository of instructional articles for a variety of tasks, which can be revised by users.
no code implementations • 21 Sep 2023 • Nicola Fanton, Agnieszka Falenska, Michael Roth
Instructional texts for specific target groups should ideally take into account the prior knowledge and needs of the readers in order to guide them efficiently to their desired goals.
1 code implementation • SemEval (NAACL) 2022 • Michael Roth, Talita Anthonio, Anna Sauer
We describe SemEval-2022 Task 7, a shared task on rating the plausibility of clarifications in instructional texts.
no code implementations • 29 Jun 2021 • Jann Michael Weinand, Russell McKenna, Heidi Heinrichs, Michael Roth, Detlef Stolten, Wolf Fichtner
Onshore wind development has historically focused on cost-efficiency, which may lead to inequitable turbine distributions and public resistance due to landscape impacts.
no code implementations • COLING 2020 • Talita Anthonio, Michael Roth
The subset of revisions considered here are noun substitutions, which often involve interesting semantic relations, including synonymy, antonymy and hypernymy.
no code implementations • LREC 2020 • Talita Anthonio, Irshad Bhat, Michael Roth
Instructional texts, such as articles in wikiHow, describe the actions necessary to accomplish a certain goal.
no code implementations • WS 2019 • Simon Ostermann, Sheng Zhang, Michael Roth, Peter Clark
This paper reports on the results of the shared tasks of the COIN workshop at EMNLP-IJCNLP 2019.
no code implementations • 22 Sep 2019 • Jinkyu Koo, Michael Roth, Saurabh Bagchi
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images.
no code implementations • WS 2019 • Lilian D. A. Wanzare, Michael Roth, Manfred Pinkal
We introduce the task of scenario detection, in which we identify references to scripts.
no code implementations • NAACL 2019 • Michael Roth, Shyam Upadhyay
It is well-known that distributional semantic approaches have difficulty in distinguishing between synonyms and antonyms (Grefenstette, 1992; Pad{\'o} and Lapata, 2003).
no code implementations • SEMEVAL 2019 • Simon Ostermann, Michael Roth, Manfred Pinkal
Half of the questions cannot be answered from the reading texts, but require the use of commonsense and, in particular, script knowledge.
no code implementations • WS 2017 • Michael Roth
Predicting the structure of a discourse is challenging because relations between discourse segments are often implicit and thus hard to distinguish computationally.
no code implementations • 13 Jun 2018 • Herman Kamper, Michael Roth
Recent work considered how images paired with speech can be used as supervision for building speech systems when transcriptions are not available.
no code implementations • SEMEVAL 2018 • Simon Ostermann, Michael Roth, Ashutosh Modi, Stefan Thater, Manfred Pinkal
This report summarizes the results of the SemEval 2018 task on machine comprehension using commonsense knowledge.
no code implementations • NAACL 2018 • Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, Dan Roth
We present a reading comprehension challenge in which questions can only be answered by taking into account information from multiple sentences.
no code implementations • LREC 2018 • Simon Ostermann, Ashutosh Modi, Michael Roth, Stefan Thater, Manfred Pinkal
We introduce a large dataset of narrative texts and questions about these texts, intended to be used in a machine comprehension task that requires reasoning using commonsense knowledge.
no code implementations • SEMEVAL 2017 • Simon Ostermann, Michael Roth, Stefan Thater, Manfred Pinkal
Script knowledge plays a central role in text understanding and is relevant for a variety of downstream tasks.
no code implementations • WS 2017 • Nasrin Mostafazadeh, Michael Roth, Annie Louis, Nathanael Chambers, James Allen
The LSDSem{'}17 shared task is the Story Cloze Test, a new evaluation for story understanding and script learning.
1 code implementation • ACL 2016 • Michael Roth, Mirella Lapata
This paper introduces a novel model for semantic role labeling that makes use of neural sequence modeling techniques.
Ranked #3 on Chinese Semantic Role Labeling on CoNLL-2009
1 code implementation • TACL 2015 • Michael Roth, Mirella Lapata
Frame semantic representations have been useful in several applications ranging from text-to-scene generation, to question answering and social network analysis.