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20212026
most citedIdentifying Machine-Paraphrased Plagiarism

40 citations · 194 across the 46 of their papers we have counts for

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32 papers · 1 filter

cs.CL2026

BabelSteering: Multilingual Safety Alignment via English Steering Vectors

Emma V. Stein, Dominik Meier, Terry Ruas +2

Large language models (LLMs) are deployed globally in high-stakes settings, yet most safety research and alignment efforts remain concentrated on English. Thus, users interacting w…

cs.CL2026

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

Niklas Bauer, Lars Benedikt Kaesberg, Akiko Aizawa +3

As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabilities is fundamental to safe…

cs.CL2026

Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains

Finn Schmidt, Jan Philip Wahle, Terry Ruas +1

Automatic evaluation metrics are central to the development of machine translation systems, yet their robustness under domain shift remains unclear. Most metrics are developed on t…

cs.CL2026

SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)

Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14

We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…

cs.CL2026

Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification

Anastasia Zhukova, Terry Ruas, Jan Philip Wahle +1

Research in CDCR remains fragmented due to heterogeneous dataset formats, varying annotation standards, and the predominance of the CDCR definition as the event coreference resolut…

cs.CL2026

Language Modeling and Understanding Through Paraphrase Generation and Detection

Jan Philip Wahle

Language enables humans to share knowledge, reason about the world, and pass on strategies for survival and innovation across generations. At the heart of this process is not just…

cs.CL2026

DimStance: Multilingual Datasets for Dimensional Stance Analysis

Jonas Becker, Liang-Chih Yu, Shamsuddeen Hassan Muhammad +14

Stance detection is an established task that classifies an author's attitude toward a specific target into categories such as Favor, Neutral, and Against. Beyond categorical stance…

cs.CL2026

DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysis

Lung-Hao Lee, Liang-Chih Yu, Natalia Loukashevich +13

Aspect-Based Sentiment Analysis (ABSA) focuses on extracting sentiment at a fine-grained aspect level and has been widely applied across real-world domains. However, existing ABSA…

cs.CL2025

Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science

Jan Philip Wahle, Krishnapriya Vishnubhotla, Bela Gipp +1

Work in Computational Affective Science and Computational Social Science explores a wide variety of research questions about people, emotions, behavior, and health. Such work often…

cs.CL2025

Overview of the Plagiarism Detection Task at PAN 2025

André Greiner-Petter, Maik Fröbe, Jan Philip Wahle +4

The generative plagiarism detection task at PAN 2025 aims at identifying automatically generated textual plagiarism in scientific articles and aligning them with their respective s…

cs.CL2025

TrojanStego: Your Language Model Can Secretly Be A Steganographic Privacy Leaking Agent

Dominik Meier, Jan Philip Wahle, Paul Röttger +2

As large language models (LLMs) become integrated into sensitive workflows, concerns grow over their potential to leak confidential information. We propose TrojanStego, a novel thr…

cs.CL2025

The Language of Interoception: Examining Embodiment and Emotion Through a Corpus of Body Part Mentions

Sophie Wu, Jan Philip Wahle, Saif M. Mohammad

This paper is the first investigation of the connection between emotion, embodiment, and everyday language in a large sample of natural language data. We created corpora of body pa…

cs.CL2025★ 1 cited

SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection

Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +18

We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource an…

cs.CL2025

Stay Focused: Problem Drift in Multi-Agent Debate

Jonas Becker, Lars Benedikt Kaesberg, Andreas Stephan +3

Multi-agent debate - multiple instances of large language models discussing problems in turn-based interaction - has shown promise for solving knowledge and reasoning tasks. Howeve…

cs.CL2025

BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages

Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45

People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…

cs.CL2024★ 1 cited

Towards Human Understanding of Paraphrase Types in Large Language Models

Dominik Meier, Jan Philip Wahle, Terry Ruas +1

Paraphrases represent a human's intuitive ability to understand expressions presented in various different ways. Current paraphrase evaluations of language models primarily use bin…

cs.CL2024★ 6 cited

Paraphrase Types Elicit Prompt Engineering Capabilities

Jan Philip Wahle, Terry Ruas, Yang Xu +1

Much of the success of modern language models depends on finding a suitable prompt to instruct the model. Until now, it has been largely unknown how variations in the linguistic ex…

cs.CL2024★ 10 cited

CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization

Frederic Kirstein, Jan Philip Wahle, Bela Gipp +1

Abstractive dialogue summarization is the task of distilling conversations into informative and concise summaries. Although reviews have been conducted on this topic, there is a la…

cs.CL2024

Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges

Jonas Becker, Jan Philip Wahle, Bela Gipp +1

Text generation has become more accessible than ever, and the growing interest in these systems, especially those using large language models, has spurred a surge in related public…

cs.CL2024★ 2 cited

What's under the hood: Investigating Automatic Metrics on Meeting Summarization

Frederic Kirstein, Jan Philip Wahle, Terry Ruas +1

Meeting summarization has become a critical task considering the increase in online interactions. While new techniques are introduced regularly, their evaluation uses metrics not d…

cs.CL2023★ 7 cited

We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields

Jan Philip Wahle, Terry Ruas, Mohamed Abdalla +2

Natural Language Processing (NLP) is poised to substantially influence the world. However, significant progress comes hand-in-hand with substantial risks. Addressing them requires…

cs.CL2023★ 7 cited

Paraphrase Types for Generation and Detection

Jan Philip Wahle, Bela Gipp, Terry Ruas

Current approaches in paraphrase generation and detection heavily rely on a single general similarity score, ignoring the intricate linguistic properties of language. This paper in…

cs.CL2023★ 17 cited

The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Research

Mohamed Abdalla, Jan Philip Wahle, Terry Ruas +4

Recent advances in deep learning methods for natural language processing (NLP) have created new business opportunities and made NLP research critical for industry development. As o…

cs.CL2023★ 1 cited

Paraphrase Detection: Human vs. Machine Content

Jonas Becker, Jan Philip Wahle, Terry Ruas +1

The growing prominence of large language models, such as GPT-4 and ChatGPT, has led to increased concerns over academic integrity due to the potential for machine-generated content…