Search Results for author:
Found 70 papers, 29 papers with code
Task Proposal: Abstractive Snippet Generation for Web Pages
We propose a shared task on abstractive snippet generation for web pages, a novel task of generating query-biased abstractive summaries for documents that are to be shown on a search results page.
Analyzing Culture-Specific Argument Structures in Learner Essays
Based on the ICLE corpus containing essays written by English learners of 16 different mother tongues, we train natural language processing models to mine argumentative discourse units (ADUs) as well as to assess the essays’ quality in terms of organization and argument strength.
Persuasiveness of News Editorials depending on Ideology and Personality
News editorials aim to shape the opinions of their readership and the general public on timely controversial issues.
“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations
As AI is more and more pervasive in everyday life, humans have an increasing demand to understand its behavior and decisions.
Identifying the Human Values behind Arguments
First experiments with the automatic classification of human values are promising, with F_1-scores up to 0. 81 and 0. 25 on average.
Argument from Old Man’s View: Assessing Social Bias in Argumentation
Social bias in language - towards genders, ethnicities, ages, and other social groups - poses a problem with ethical impact for many NLP applications.
Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
Dialects introduce syntactic and lexical variations in language that occur in regional or social groups.
LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback
Ensuring that online discussions are civil and productive is a major challenge for social media platforms.
Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation
We evaluate both the AES performance that LLMs can achieve with prompting only and the helpfulness of the generated essay feedback.
A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality
When combined with automatic essay scoring, interactions of the argumentative structure and quality scores can be exploited for comprehensive writing support.
Argument Quality Assessment in the Age of Instruction-Following Large Language Models
The computational treatment of arguments on controversial issues has been subject to extensive NLP research, due to its envisioned impact on opinion formation, decision making, writing education, and the like.
Modeling the Quality of Dialogical Explanations
In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee's side.
Mind the Gap: Automated Corpus Creation for Enthymeme Detection and Reconstruction in Learner Arguments
Writing strong arguments can be challenging for learners.
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks
The fields of both Natural Language Processing (NLP) and Automated Machine Learning (AutoML) have achieved remarkable results over the past years.
To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support
Optimizing the phrasing of argumentative text is crucial in higher education and professional development.
Modeling Appropriate Language in Argumentation
Online discussion moderators must make ad-hoc decisions about whether the contributions of discussion participants are appropriate or should be removed to maintain civility.
Perspectives on Large Language Models for Relevance Judgment
When asked, large language models (LLMs) like ChatGPT claim that they can assist with relevance judgments but it is not clear whether automated judgments can reliably be used in evaluations of retrieval systems.
The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments
We present the Touch\'e23-ValueEval Dataset for Identifying Human Values behind Arguments.
Conclusion-based Counter-Argument Generation
In real-world debates, the most common way to counter an argument is to reason against its main point, that is, its conclusion.
Claim Optimization in Computational Argumentation
This requires the use of clear and fluent claims relevant to the given debate.
No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media
To cover the whole spectrum of political bias in the US, we collect 500k articles and review psychology literature with respect to expected social bias.
"Mama Always Had a Way of Explaining Things So I Could Understand'': A Dialogue Corpus for Learning to Construct Explanations
As AI is more and more pervasive in everyday life, humans have an increasing demand to understand its behavior and decisions.
The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments
An audience's prior beliefs and morals are strong indicators of how likely they will be affected by a given argument.
Assessing the Sufficiency of Arguments through Conclusion Generation
An argument whose premises make its conclusion rationally worthy to be drawn is called sufficient in argument quality research.
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments.
Controlled Neural Sentence-Level Reframing of News Articles
Reframing is related to adapting style and sentiment, which can be tackled with neural text generation techniques.
Employing Argumentation Knowledge Graphs for Neural Argument Generation
Generating high-quality arguments, while being challenging, may benefit a wide range of downstream applications, such as writing assistants and argument search engines.
Syntopical Graphs for Computational Argumentation Tasks
Approaches to computational argumentation tasks such as stance detection and aspect detection have largely focused on the text of independent claims, losing out on potentially valuable context provided by the rest of the collection.
Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation
Despite extensive research efforts in recent years, computational argumentation (CA) remains one of the most challenging areas of natural language processing.
Generating Informative Conclusions for Argumentative Texts
Third, insights are provided into the suitability of our corpus for the task, the differences between the two generation paradigms, the trade-off between informativeness and conciseness, and the impact of encoding argumentative knowledge.
Argument Undermining: Counter-Argument Generation by Attacking Weak Premises
We hypothesize that identifying the argument's weak premises is key to effective countering.
Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale
However, even if different claims share the same stance on the same topic, their assessment depends on the prior perception and weighting of the different aspects of the topic being discussed.
Belief-based Generation of Argumentative Claims
In this work, we aim to bridge this gap by studying the task of belief-based claim generation: Given a controversial topic and a set of beliefs, generate an argumentative claim tailored to the beliefs.
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles.
Mining Crowdsourcing Problems from Discussion Forums of Workers
Crowdsourcing is used in academia and industry to solve tasks that are easy for humans but hard for computers, in natural language processing mostly to annotate data.
Argument from Old Man's View: Assessing Social Bias in Argumentation
Social bias in language - towards genders, ethnicities, ages, and other social groups - poses a problem with ethical impact for many NLP applications.
Semi-Supervised Cleansing of Web Argument Corpora
Debate portals and similar web platforms constitute one of the main text sources in computational argumentation research and its applications.
Intrinsic Quality Assessment of Arguments
Several quality dimensions of natural language arguments have been investigated.
Detecting Media Bias in News Articles using Gaussian Bias Distributions
In particular, we utilize the probability distributions of the frequency, positions, and sequential order of lexical and informational sentence-level bias in a Gaussian Mixture Model.
Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity
Media organizations bear great reponsibility because of their considerable influence on shaping beliefs and positions of our society.
Target Inference in Argument Conclusion Generation
In particular, we argue here that a decisive step is to infer a conclusion{'}s target, and we hypothesize that this target is related to the premises{'} targets.
Analyzing the Persuasive Effect of Style in News Editorial Argumentation
News editorials argue about political issues in order to challenge or reinforce the stance of readers with different ideologies.
Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition
Many discussions on online platforms suffer from users offending others by using abusive terminology, threatening each other, or being sarcastic.
Modeling Frames in Argumentation
In general, we call a set of arguments that focus on the same aspect a frame.
Computational Argumentation Synthesis as a Language Modeling Task
Synthesis approaches in computational argumentation so far are restricted to generating claim-like argument units or short summaries of debates.
Visualization of the Topic Space of Argument Search Results in args.me
In times of fake news and alternative facts, pro and con arguments on controversial topics are of increasing importance.
Learning to Flip the Bias of News Headlines
This paper introduces the task of {``}flipping{''} the bias of news articles: Given an article with a political bias (left or right), generate an article with the same topic but opposite bias.
Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus
Analyzing the corpus, we find that annotators with different orientation disagree on the effect significantly.
Argumentation Synthesis following Rhetorical Strategies
In this paper, we model rhetorical strategies for the computational synthesis of effective argumentation.
Retrieval of the Best Counterargument without Prior Topic Knowledge
Given any argument on any controversial topic, how to counter it?
Modeling Deliberative Argumentation Strategies on Wikipedia
This paper studies how the argumentation strategies of participants in deliberative discussions can be supported computationally.
SemEval-2018 Task 12: The Argument Reasoning Comprehension Task
A natural language argument is composed of a claim as well as reasons given as premises for the claim.
Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation
Arguing without committing a fallacy is one of the main requirements of an ideal debate.
The Impact of Modeling Overall Argumentation with Tree Kernels
Several approaches have been proposed to model either the explicit sequential structure of an argumentative text or its implicit hierarchical structure.
Patterns of Argumentation Strategies across Topics
This paper presents an analysis of argumentation strategies in news editorials within and across topics.
Building an Argument Search Engine for the Web
Computational argumentation is expected to play a critical role in the future of web search.
Unit Segmentation of Argumentative Texts
The segmentation of an argumentative text into argument units and their non-argumentative counterparts is the first step in identifying the argumentative structure of the text.
The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants
On this basis, we present a new challenging task, the argument reasoning comprehension task.
Argumentation Quality Assessment: Theory vs. Practice
Argumentation quality is viewed differently in argumentation theory and in practical assessment approaches.
``PageRank'' for Argument Relevance
Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics.
Computational Argumentation Quality Assessment in Natural Language
Research on computational argumentation faces the problem of how to automatically assess the quality of an argument or argumentation.
WAT-SL: A Customizable Web Annotation Tool for Segment Labeling
A frequent type of annotations in text corpora are labeled text segments.
A News Editorial Corpus for Mining Argumentation Strategies
Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude.
Using Argument Mining to Assess the Argumentation Quality of Essays
In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays.
