Search Results for author:
Found 96 papers, 35 papers with code
CausalQA: A Benchmark for Causal Question Answering
At least 5% of questions submitted to search engines ask about cause-effect relationships in some way.
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.
Image Retrieval for Arguments Using Stance-Aware Query Expansion
Many forms of argumentation employ images as persuasive means, but research in argument mining has been focused on verbal argumentation so far.
Analyzing Persuasion Strategies of Debaters on Social Media
Existing studies on the analysis of persuasion in online discussions focus on investigating the effectiveness of comments in discussions and ignore the analysis of the effectiveness of debaters over multiple discussions.
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.
Mining Health-related Cause-Effect Statements with High Precision at Large Scale
An efficient assessment of the health relatedness of text passages is important to mine the web at scale to conduct health sociological analyses or to develop a health search engine.
Language Models as Context-sensitive Word Search Engines
Context-sensitive word search engines are writing assistants that support word choice, phrasing, and idiomatic language use by indexing large-scale n-gram collections and implementing a wildcard search.
Style Analysis of Argumentative Texts by Mining Rhetorical Devices
To this end, we developed and evaluated a grammar-based approach for identifying 26 syntax-based devices.
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.
A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking
Cross-encoders distilled from large language models (LLMs) are often more effective re-rankers than cross-encoders fine-tuned on manually labeled data.
Are Large Language Models Reliable Argument Quality Annotators?
In this paper, we study the potential of using state-of-the-art large language models (LLMs) as proxies for argument quality annotators.
If there's a Trigger Warning, then where's the Trigger? Investigating Trigger Warnings at the Passage Level
Trigger warnings are labels that preface documents with sensitive content if this content could be perceived as harmful by certain groups of readers.
Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders
Existing cross-encoder re-rankers can be categorized as pointwise, pairwise, or listwise models.
Task-Oriented Paraphrase Analytics
Since paraphrasing is an ill-defined task, the term "paraphrasing" covers text transformation tasks with different characteristics.
Detecting Generated Native Ads in Conversational Search
In this paper, we thus take a first step to investigate whether LLMs can also be used as a countermeasure, i. e., to block generated native ads.
Assisted Knowledge Graph Authoring: Human-Supervised Knowledge Graph Construction from Natural Language
Encyclopedic knowledge graphs, such as Wikidata, host an extensive repository of millions of knowledge statements.
Argumentation in Waltz's "Emerging Structure of International Politics''
We present an annotation scheme for argumentative and domain-specific aspects of scholarly articles on the theory of International Relations.
Evaluating Generative Ad Hoc Information Retrieval
To lay a foundation for developing new evaluation methods for generative retrieval systems, we survey the relevant literature from the fields of information retrieval and natural language processing, identify search tasks and system architectures in generative retrieval, develop a new user model, and study its operationalization.
Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels
The reliability of supervised machine learning systems depends on the accuracy and availability of ground truth labels.
Ranked #1 on
Object Detection
on TexBiG 2023 test
The Information Retrieval Experiment Platform
Standardization is achieved when a retrieval approach implements PyTerrier's interfaces and the input and output of an experiment are compatible with ir_datasets and ir_measures.
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 Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives
The Archive Query Log (AQL) is a previously unused, comprehensive query log collected at the Internet Archive over the last 25 years.
The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments
We present the Touch\'e23-ValueEval Dataset for Identifying Human Values behind Arguments.
Paraphrase Acquisition from Image Captions
We propose to use image captions from the Web as a previously underutilized resource for paraphrases (i. e., texts with the same "message") and to create and analyze a corresponding dataset.
Topic Ontologies for Arguments
Many computational argumentation tasks, like stance classification, are topic-dependent: the effectiveness of approaches to these tasks significantly depends on whether the approaches were trained on arguments from the same topics as those they are tested on.
The Infinite Index: Information Retrieval on Generative Text-To-Image Models
Conditional generative models such as DALL-E and Stable Diffusion generate images based on a user-defined text, the prompt.
SMAuC -- The Scientific Multi-Authorship Corpus
The rapidly growing volume of scientific publications offers an interesting challenge for research on methods for analyzing the authorship of documents with one or more authors.
Differential Bias: On the Perceptibility of Stance Imbalance in Argumentation
We see the problem not in the complexity of interpreting language phenomena but in the diversity of sociocultural backgrounds of the readers, which cannot be handled uniformly: To decide whether a text has crossed the proverbial line between non-biased and biased is subjective.
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s Alpha
The method is adjustable with regard to evaluation strictness, and it can be used in 2D or 3D as well as for a variety of tasks such as semantic segmentation, instance segmentation, and 3D point cloud segmentation.
Ranked #1 on
Instance Segmentation
on TexBiG 2022 test
Trigger Warnings: Bootstrapping a Violence Detector for FanFiction
We present the first dataset and evaluation results on a newly defined computational task of trigger warning assignment.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
STEREO: Scientific Text Reuse in Open Access Publications
We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications.
FastWARC: Optimizing Large-Scale Web Archive Analytics
Web search and other large-scale web data analytics rely on processing archives of web pages stored in a standardized and efficient format.
The Impact of Main Content Extraction on Near-Duplicate Detection
Commercial web search engines employ near-duplicate detection to ensure that users see each relevant result only once, albeit the underlying web crawls typically include (near-)duplicates of many web pages.
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.
Towards Axiomatic Explanations for Neural Ranking Models
We investigate whether one can explain the behavior of neural ranking models in terms of their congruence with well understood principles of document ranking by using established theories from axiomatic IR.
News Editorials: Towards Summarizing Long Argumentative Texts
With Webis-EditorialSum-2020, we present a corpus of 1330 carefully curated summaries for 266 news editorials.
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.
Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness
Predicting the persuasiveness of arguments has applications as diverse as writing assistance, essay scoring, and advertising.
Crawling and Preprocessing Mailing Lists At Scale for Dialog Analysis
This paper introduces the Webis Gmane Email Corpus 2019, the largest publicly available and fully preprocessed email corpus to date.
Efficient Pairwise Annotation of Argument Quality
We present an efficient annotation framework for argument quality, a feature difficult to be measured reliably as per previous work.
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.
The Importance of Suppressing Domain Style in Authorship Analysis
The prerequisite of many approaches to authorship analysis is a representation of writing style.
Conversational Search -- A Report from Dagstuhl Seminar 19461
Dagstuhl Seminar 19461 "Conversational Search" was held on 10-15 November 2019.
Abstractive Snippet Generation
An abstractive snippet is an originally created piece of text to summarize a web page on a search engine results page.
Ranked #1 on
Text Summarization
on Webis-Snippet-20 Corpus
Modeling Frames in Argumentation
In general, we call a set of arguments that focus on the same aspect a frame.
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.
Towards Summarization for Social Media - Results of the TL;DR Challenge
In this paper, we report on the results of the TL;DR challenge, discussing an extensive manual evaluation of the expected properties of a good summary based on analyzing the comments provided by human annotators.
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.
Continuous Quality Control and Advanced Text Segment Annotation with WAT-SL 2.0
Today{'}s widely used annotation tools were designed for annotating typically short textual mentions of entities or relations, making their interface cumbersome to use for long(er) stretches of text, e. g, sentences running over several lines in a document.
Bias Analysis and Mitigation in the Evaluation of Authorship Verification
The PAN series of shared tasks is well known for its continuous and high quality research in the field of digital text forensics.
Heuristic Authorship Obfuscation
Authorship verification is the task of determining whether two texts were written by the same author.
Celebrity Profiling
Celebrities are among the most prolific users of social media, promoting their personas and rallying followers.
SemEval-2019 Task 4: Hyperpartisan News Detection
Hyperpartisan news is news that takes an extreme left-wing or right-wing standpoint.
Generalizing Unmasking for Short Texts
Authorship verification is the problem of inferring whether two texts were written by the same author.
The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength
Clickbait has grown to become a nuisance to social media users and social media operators alike.
Task Proposal: The TL;DR Challenge
The TL;DR challenge fosters research in abstractive summarization of informal text, the largest and fastest-growing source of textual data on the web, which has been overlooked by summarization research so far.
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.
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.
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.
Safe Stream-Based Programming with Refinement Types
Our key insight is that the fluent APIs of stream-processing frameworks enable the tracking of threads via type-refinement, making it possible to reason automatically about what thread a piece of code runs on -- a difficult problem in general.
Software Engineering Programming Languages
Argumentation Synthesis following Rhetorical Strategies
In this paper, we model rhetorical strategies for the computational synthesis of effective argumentation.
Crowdsourcing a Large Corpus of Clickbait on Twitter
To address the urging task of clickbait detection, we constructed a new corpus of 38, 517 annotated Twitter tweets, the Webis Clickbait Corpus 2017.
Modeling Deliberative Argumentation Strategies on Wikipedia
This paper studies how the argumentation strategies of participants in deliberative discussions can be supported computationally.
Retrieval of the Best Counterargument without Prior Topic Knowledge
Given any argument on any controversial topic, how to counter it?
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.
Heuristic Feature Selection for Clickbait Detection
We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017.
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.
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.
TL;DR: Mining Reddit to Learn Automatic Summarization
Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data.
Patterns of Argumentation Strategies across Topics
This paper presents an analysis of argumentation strategies in news editorials within and across topics.
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.
WAT-SL: A Customizable Web Annotation Tool for Segment Labeling
A frequent type of annotations in text corpora are labeled text segments.
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.
``PageRank'' for Argument Relevance
Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics.
A Stylometric Inquiry into Hyperpartisan and Fake News
The articles originated from 9 well-known political publishers, 3 each from the mainstream, the hyperpartisan left-wing, and the hyperpartisan right-wing.
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.
Cross-Lingual Adaptation using Structural Correspondence Learning
From these correspondences a cross-lingual representation is created that enables the transfer of classification knowledge from the source to the target language.
