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Found 34 papers, 3 papers with code
UnImplicit Shared Task Report: Detecting Clarification Requirements in Instructional Text
This paper describes the data, task setup, and results of the shared task at the First Workshop on Understanding Implicit and Underspecified Language (UnImplicit).
Resolving Implicit References in Instructional Texts
The usage of (co-)referring expressions in discourse contributes to the coherence of a text.
Predicting Coreference in Abstract Meaning Representations
This work addresses coreference resolution in Abstract Meaning Representation (AMR) graphs, a popular formalism for semantic parsing.
Clarifying Implicit and Underspecified Phrases in Instructional Text
In this paper, we present a data set of such phrases in English from instructional texts together with multiple possible clarifications.
Towards Modeling Revision Requirements in wikiHow Instructions
wikiHow is a resource of how-to guidesthat describe the steps necessary to accomplish a goal.
A Computational Analysis of Vagueness in Revisions of Instructional Texts
WikiHow is an open-domain repository of instructional articles for a variety of tasks, which can be revised by users.
How-to Guides for Specific Audiences: A Corpus and Initial Findings
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.
SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts
We describe SemEval-2022 Task 7, a shared task on rating the plausibility of clarifications in instructional texts.
Exploring the trilemma of cost-efficient, equitable and publicly acceptable onshore wind expansion planning
Onshore wind development has historically focused on cost-efficiency, which may lead to inequitable turbine distributions and public resistance due to landscape impacts.
What Can We Learn from Noun Substitutions in Revision Histories?
The subset of revisions considered here are noun substitutions, which often involve interesting semantic relations, including synonymy, antonymy and hypernymy.
wikiHowToImprove: A Resource and Analyses on Edits in Instructional Texts
Instructional texts, such as articles in wikiHow, describe the actions necessary to accomplish a certain goal.
Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report
This paper reports on the results of the shared tasks of the COIN workshop at EMNLP-IJCNLP 2019.
HAWKEYE: Adversarial Example Detector for Deep Neural Networks
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images.
Detecting Everyday Scenarios in Narrative Texts
We introduce the task of scenario detection, in which we identify references to scripts.
Combining Discourse Markers and Cross-lingual Embeddings for Synonym--Antonym Classification
It is well-known that distributional semantic approaches have difficulty in distinguishing between synonyms and antonyms (Grefenstette, 1992; Pad{\'o} and Lapata, 2003).
MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants
Half of the questions cannot be answered from the reading texts, but require the use of commonsense and, in particular, script knowledge.
Role Semantics for Better Models of Implicit Discourse Relations
Predicting the structure of a discourse is challenging because relations between discourse segments are often implicit and thus hard to distinguish computationally.
Visually grounded cross-lingual keyword spotting in speech
Recent work considered how images paired with speech can be used as supervision for building speech systems when transcriptions are not available.
SemEval-2018 Task 11: Machine Comprehension Using Commonsense Knowledge
This report summarizes the results of the SemEval 2018 task on machine comprehension using commonsense knowledge.
Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences
We present a reading comprehension challenge in which questions can only be answered by taking into account information from multiple sentences.
MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge
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.
Aligning Script Events with Narrative Texts
Script knowledge plays a central role in text understanding and is relevant for a variety of downstream tasks.
LSDSem 2017 Shared Task: The Story Cloze Test
The LSDSem{'}17 shared task is the Story Cloze Test, a new evaluation for story understanding and script learning.
Neural Semantic Role Labeling with Dependency Path Embeddings
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
Context-aware Frame-Semantic Role Labeling
Frame semantic representations have been useful in several applications ranging from text-to-scene generation, to question answering and social network analysis.
