Search Results for author: Martin Potthast

Found 75 papers, 40 papers with code

Language Models as Context-sensitive Word Search Engines

1 code implementation In2Writing (ACL) 2022 Matti Wiegmann, Michael Völske, Benno Stein, Martin Potthast

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.

Language Modelling

Image Retrieval for Arguments Using Stance-Aware Query Expansion

no code implementations EMNLP (ArgMining) 2021 Johannes Kiesel, Nico Reichenbach, Benno Stein, Martin Potthast

Many forms of argumentation employ images as persuasive means, but research in argument mining has been focused on verbal argumentation so far.

Argument Mining Argument Retrieval +2

Mining Health-related Cause-Effect Statements with High Precision at Large Scale

1 code implementation COLING 2022 Ferdinand Schlatt, Dieter Bettin, Matthias Hagen, Benno Stein, Martin Potthast

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.

Task Proposal: Abstractive Snippet Generation for Web Pages

no code implementations INLG (ACL) 2020 Shahbaz Syed, Wei-Fan Chen, Matthias Hagen, Benno Stein, Henning Wachsmuth, Martin Potthast

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.

Abstractive Text Summarization

Casting the Same Sentiment Classification Problem

1 code implementation Findings (EMNLP) 2021 Erik Körner, Ahmad Dawar Hakimi, Gerhard Heyer, Martin Potthast

We introduce and study a problem variant of sentiment analysis, namely the “same sentiment classification problem”, where, given a pair of texts, the task is to determine if they have the same sentiment, disregarding the actual sentiment polarity.

Classification Language Modelling +2

TL;DR Progress: Multi-faceted Literature Exploration in Text Summarization

1 code implementation10 Feb 2024 Shahbaz Syed, Khalid Al-Khatib, Martin Potthast

This paper presents TL;DR Progress, a new tool for exploring the literature on neural text summarization.

Text Summarization

Detecting Generated Native Ads in Conversational Search

no code implementations7 Feb 2024 Sebastian Schmidt, Ines Zelch, Janek Bevendorff, Benno Stein, Matthias Hagen, Martin Potthast

It is only a small step to also use this technology to generate and integrate advertising within these answers - instead of placing ads separately from the organic search results.

Conversational Search Sentence

Zero-shot Generative Large Language Models for Systematic Review Screening Automation

no code implementations12 Jan 2024 Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon

Systematic reviews are crucial for evidence-based medicine as they comprehensively analyse published research findings on specific questions.

Citance-Contextualized Summarization of Scientific Papers

1 code implementation4 Nov 2023 Shahbaz Syed, Ahmad Dawar Hakimi, Khalid Al-Khatib, Martin Potthast

We propose a new contextualized summarization approach that can generate an informative summary conditioned on a given sentence containing the citation of a reference (a so-called "citance").


Indicative Summarization of Long Discussions

1 code implementation3 Nov 2023 Shahbaz Syed, Dominik Schwabe, Khalid Al-Khatib, Martin Potthast

Online forums encourage the exchange and discussion of different stances on many topics.

Prompt Engineering

Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation

1 code implementation11 Sep 2023 Shuai Wang, Harrisen Scells, Martin Potthast, Bevan Koopman, Guido Zuccon

Our best approach is not only viable based on the information available at the time of screening, but also has similar effectiveness to the final title.

Natural Language Queries

Manipulating Embeddings of Stable Diffusion Prompts

1 code implementation23 Aug 2023 Niklas Deckers, Julia Peters, Martin Potthast

(3) Changing the embedding of the prompt to include information that the user has seen in a particular seed but finds difficult to describe in the prompt.

Navigate Prompt Engineering

OpinionConv: Conversational Product Search with Grounded Opinions

1 code implementation8 Aug 2023 Vahid Sadiri Javadi, Martin Potthast, Lucie Flek

This is also true in sales conversations, where a customer and a sales assistant exchange facts and opinions about products.

Decision Making

GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration

1 code implementation2 Jun 2023 Aleksandra Piktus, Odunayo Ogundepo, Christopher Akiki, Akintunde Oladipo, Xinyu Zhang, Hailey Schoelkopf, Stella Biderman, Martin Potthast, Jimmy Lin

We discuss how Pyserini - a widely used toolkit for reproducible IR research can be integrated with the Hugging Face ecosystem of open-source AI libraries and artifacts.

Information Retrieval Retrieval

The Information Retrieval Experiment Platform

1 code implementation30 May 2023 Maik Fröbe, Jan Heinrich Reimer, Sean MacAvaney, Niklas Deckers, Simon Reich, Janek Bevendorff, Benno Stein, Matthias Hagen, Martin Potthast

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.

Information Retrieval Retrieval

Modeling Appropriate Language in Argumentation

1 code implementation24 May 2023 Timon Ziegenbein, Shahbaz Syed, Felix Lange, Martin Potthast, Henning Wachsmuth

Online discussion moderators must make ad-hoc decisions about whether the contributions of discussion participants are appropriate or should be removed to maintain civility.

Using Language Models on Low-end Hardware

no code implementations3 May 2023 Fabian Ziegner, Janos Borst, Andreas Niekler, Martin Potthast

This paper evaluates the viability of using fixed language models for training text classification networks on low-end hardware.

Language Modelling Multi-Label Classification +2

Perspectives on Large Language Models for Relevance Judgment

no code implementations13 Apr 2023 Guglielmo Faggioli, Laura Dietz, Charles Clarke, Gianluca Demartini, Matthias Hagen, Claudia Hauff, Noriko Kando, Evangelos Kanoulas, Martin Potthast, Benno Stein, Henning Wachsmuth

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.


Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face

1 code implementation28 Feb 2023 Christopher Akiki, Odunayo Ogundepo, Aleksandra Piktus, Xinyu Zhang, Akintunde Oladipo, Jimmy Lin, Martin Potthast

We present Spacerini, a modular framework for seamless building and deployment of interactive search applications, designed to facilitate the qualitative analysis of large scale research datasets.


Paraphrase Acquisition from Image Captions

1 code implementation26 Jan 2023 Marcel Gohsen, Matthias Hagen, Martin Potthast, Benno Stein

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.

Image Captioning

Topic Ontologies for Arguments

no code implementations23 Jan 2023 Yamen Ajjour, Johannes Kiesel, Benno Stein, Martin Potthast

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.

Stance Classification Topic coverage

SMAuC -- The Scientific Multi-Authorship Corpus

no code implementations4 Nov 2022 Janek Bevendorff, Philipp Sauer, Lukas Gienapp, Wolfgang Kircheis, Erik Körner, Benno Stein, Martin Potthast

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.

Summary Workbench: Unifying Application and Evaluation of Text Summarization Models

1 code implementation18 Oct 2022 Shahbaz Syed, Dominik Schwabe, Martin Potthast

This paper presents Summary Workbench, a new tool for developing and evaluating text summarization models.

Text Summarization

Differential Bias: On the Perceptibility of Stance Imbalance in Argumentation

no code implementations13 Oct 2022 Alonso Palomino, Martin Potthast, Khalid Al-Khatib, Benno Stein

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.


Trigger Warnings: Bootstrapping a Violence Detector for FanFiction

no code implementations9 Sep 2022 Magdalena Wolska, Christopher Schröder, Ole Borchardt, Benno Stein, Martin Potthast

We present the first dataset and evaluation results on a newly defined computational task of trigger warning assignment.

Binary Classification

Sparse Pairwise Re-ranking with Pre-trained Transformers

1 code implementation10 Jul 2022 Lukas Gienapp, Maik Fröbe, Matthias Hagen, Martin Potthast

Pairwise re-ranking models predict which of two documents is more relevant to a query and then aggregate a final ranking from such preferences.

Passage Ranking Re-Ranking +1

How Train-Test Leakage Affects Zero-shot Retrieval

1 code implementation29 Jun 2022 Maik Fröbe, Christopher Akiki, Martin Potthast, Matthias Hagen

We investigate the impact of this unintended train-test leakage by training neural retrieval models on combinations of a fixed number of MS MARCO / ORCAS queries that are highly similar to the actual test queries and an increasing number of other queries.

Retrieval Test

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

3 code implementations9 Jun 2022 Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, César Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodola, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocoń, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Şenel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramírez Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima, Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, ZiRui Wang, Ziyi Wu

BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.

Common Sense Reasoning Math +1

Clickbait Spoiling via Question Answering and Passage Retrieval

1 code implementation ACL 2022 Matthias Hagen, Maik Fröbe, Artur Jurk, Martin Potthast

We introduce and study the task of clickbait spoiling: generating a short text that satisfies the curiosity induced by a clickbait post.

Passage Retrieval Question Answering +1

Tracking Discourse Influence in Darknet Forums

1 code implementation4 Feb 2022 Christopher Akiki, Lukas Gienapp, Martin Potthast

This technical report documents our efforts in addressing the tasks set forth by the 2021 AMoC (Advanced Modelling of Cyber Criminal Careers) Hackathon.

STEREO: Scientific Text Reuse in Open Access Publications

1 code implementation22 Dec 2021 Lukas Gienapp, Wolfgang Kircheis, Bjarne Sievers, Benno Stein, Martin Potthast

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

1 code implementation22 Nov 2021 Janek Bevendorff, Martin Potthast, Benno Stein

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

no code implementations21 Nov 2021 Maik Fröbe, Matthias Hagen, Janek Bevendorff, Michael Völske, Benno Stein, Christopher Schröder, Robby Wagner, Lukas Gienapp, Martin Potthast

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.

Information Retrieval Retrieval

BERTian Poetics: Constrained Composition with Masked LMs

1 code implementation28 Oct 2021 Christopher Akiki, Martin Potthast

Masked language models have recently been interpreted as energy-based sequence models that can be generated from using a Metropolis--Hastings sampler.

Modeling Proficiency with Implicit User Representations

no code implementations15 Oct 2021 Kim Breitwieser, Allison Lahnala, Charles Welch, Lucie Flek, Martin Potthast

We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some level of proficiency.

Summary Explorer: Visualizing the State of the Art in Text Summarization

1 code implementation EMNLP (ACL) 2021 Shahbaz Syed, Tariq Yousef, Khalid Al-Khatib, Stefan Jänicke, Martin Potthast

This paper introduces Summary Explorer, a new tool to support the manual inspection of text summarization systems by compiling the outputs of 55~state-of-the-art single document summarization approaches on three benchmark datasets, and visually exploring them during a qualitative assessment.

Document Summarization Position

Generating Informative Conclusions for Argumentative Texts

1 code implementation Findings (ACL) 2021 Shahbaz Syed, Khalid Al-Khatib, Milad Alshomary, Henning Wachsmuth, Martin Potthast

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.


Crawling and Preprocessing Mailing Lists At Scale for Dialog Analysis

no code implementations ACL 2020 Janek Bevendorff, Khalid Al Khatib, Martin Potthast, Benno Stein

This paper introduces the Webis Gmane Email Corpus 2019, the largest publicly available and fully preprocessed email corpus to date.

Target Inference in Argument Conclusion Generation

no code implementations ACL 2020 Milad Alshomary, Shahbaz Syed, Martin Potthast, Henning Wachsmuth

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.

Efficient Pairwise Annotation of Argument Quality

no code implementations ACL 2020 Lukas Gienapp, Benno Stein, Matthias Hagen, Martin Potthast

We present an efficient annotation framework for argument quality, a feature difficult to be measured reliably as per previous work.

Abstractive Snippet Generation

1 code implementation25 Feb 2020 Wei-Fan Chen, Shahbaz Syed, Benno Stein, Matthias Hagen, Martin Potthast

An abstractive snippet is an originally created piece of text to summarize a web page on a search engine results page.

Text Summarization

Common Conversational Community Prototype: Scholarly Conversational Assistant

no code implementations19 Jan 2020 Krisztian Balog, Lucie Flekova, Matthias Hagen, Rosie Jones, Martin Potthast, Filip Radlinski, Mark Sanderson, Svitlana Vakulenko, Hamed Zamani

This paper discusses the potential for creating academic resources (tools, data, and evaluation approaches) to support research in conversational search, by focusing on realistic information needs and conversational interactions.

Conversational Search

Towards Summarization for Social Media - Results of the TL;DR Challenge

no code implementations WS 2019 Shahbaz Syed, Michael V{\"o}lske, Nedim Lipka, Benno Stein, Hinrich Sch{\"u}tze, Martin Potthast

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.

Bias Analysis and Mitigation in the Evaluation of Authorship Verification

1 code implementation ACL 2019 Janek Bevendorff, Matthias Hagen, Benno Stein, Martin Potthast

The PAN series of shared tasks is well known for its continuous and high quality research in the field of digital text forensics.

Authorship Verification Benchmarking

Heuristic Authorship Obfuscation

1 code implementation ACL 2019 Janek Bevendorff, Martin Potthast, Matthias Hagen, Benno Stein

Authorship verification is the task of determining whether two texts were written by the same author.

Authorship Verification

Celebrity Profiling

1 code implementation ACL 2019 Matti Wiegmann, Benno Stein, Martin Potthast

Celebrities are among the most prolific users of social media, promoting their personas and rallying followers.

Gender Prediction Occupation prediction +1

Task Proposal: The TL;DR Challenge

no code implementations WS 2018 Shahbaz Syed, Michael V{\"o}lske, Martin Potthast, Nedim Lipka, Benno Stein, Hinrich Sch{\"u}tze

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.

Abstractive Text Summarization Information Retrieval +1

CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

no code implementations CONLL 2018 Daniel Zeman, Jan Haji{\v{c}}, Martin Popel, Martin Potthast, Milan Straka, Filip Ginter, Joakim Nivre, Slav Petrov

Every year, the Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets.

Dependency Parsing Morphological Analysis +2

Crowdsourcing a Large Corpus of Clickbait on Twitter

no code implementations COLING 2018 Martin Potthast, Tim Gollub, Kristof Komlossy, Sebastian Schuster, Matti Wiegmann, Garces Fern, Erika Patricia ez, Matthias Hagen, Benno Stein

To address the urging task of clickbait detection, we constructed a new corpus of 38, 517 annotated Twitter tweets, the Webis Clickbait Corpus 2017.

Clickbait Detection

Heuristic Feature Selection for Clickbait Detection

no code implementations4 Feb 2018 Matti Wiegmann, Michael Völske, Benno Stein, Matthias Hagen, Martin Potthast

We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017.

Clickbait Detection Feature Engineering +2

TL;DR: Mining Reddit to Learn Automatic Summarization

no code implementations WS 2017 Michael V{\"o}lske, Martin Potthast, Shahbaz Syed, Benno Stein

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.

Abstractive Text Summarization Document Summarization

A Stylometric Inquiry into Hyperpartisan and Fake News

1 code implementation ACL 2018 Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, Benno Stein

The articles originated from 9 well-known political publishers, 3 each from the mainstream, the hyperpartisan left-wing, and the hyperpartisan right-wing.

Authorship Verification Fake News Detection +1

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