Jan Philip Wahle — accepted AI-conference papers

2025

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

Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Jan Philip Wahle, Terry Ruas, Meriem Beloucif +42

ACL 2025long

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 within NLP and beyond, most work in this area has focused on high-resource languages. This has led to significant disparities…

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2025

CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization (Abstract Reprint)

Frederic Kirstein, Jan Philip Wahle, Bela Gipp, Terry Ruas

IJCAI 2025

Abstractive dialogue summarization is the task of distilling conversations into informative and concise summaries. Although focused reviews have been conducted on this topic, there is a lack of comprehensive work that details the core challenges of dialogue summarization, unifies the differing under

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2025

Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields

Jan Philip Wahle, Terry Lima Ruas, Mohamed Abdalla, Bela Gipp, Saif M. Mohammad

COLING 2025main

This study examines the tendency to cite older work across 20 fields of study over 43 years (1980–2023). We put NLP’s propensity to cite older work in the context of these 20 other fields to analyze whether NLP shows similar temporal citation patterns to them over time or whether differences can be…

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2025

SPaRC: A Spatial Pathfinding Reasoning Challenge

Lars Benedikt Kaesberg, Jan Philip Wahle, Terry Ruas, Bela Gipp

EMNLP 2025

Existing reasoning datasets saturate and fail to test abstract, multi-step problems, especially pathfinding and complex rule constraint satisfaction. We introduce SPaRC (Spatial Pathfinding Reasoning Challenge), a dataset of 1,000 2D grid pathfinding puzzles to evaluate spatial and rule-based reason

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2025

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

Sophie Wu, Jan Philip Wahle, Saif M. Mohammad

EMNLP 2025

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 part mentions (BPMs) in online English text (blog posts and tweets). This includes a subset featuring human annotations fo

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2025

Towards Human Understanding of Paraphrase Types in Large Language Models

Dominik Meier, Jan Philip Wahle, Terry Lima Ruas, Bela Gipp

COLING 2025main

Paraphrases represent a human’s intuitive ability to understand expressions presented in various different ways. Current paraphrase evaluations of language models primarily use binary approaches, offering limited interpretability of specific text changes. Atomic paraphrase types (APT) decompose para…

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2025

Voting or Consensus? Decision-Making in Multi-Agent Debate

Lars Benedikt Kaesberg, Jonas Becker, Jan Philip Wahle, Terry Ruas, Bela Gipp

ACL 2025finding

Much of the success of multi-agent debates depends on carefully choosing the right parameters. The decision-making protocol stands out as it can highly impact final model answers, depending on how decisions are reached. Systematic comparison of decision protocols is difficult because many studies al…

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2025

You need to MIMIC to get FAME: Solving Meeting Transcript Scarcity with Multi-Agent Conversations

Frederic Kirstein, Muneeb Khan, Jan Philip Wahle, Terry Ruas, Bela Gipp

ACL 2025finding

Meeting summarization suffers from limited high-quality data, mainly due to privacy restrictions and expensive collection processes. We address this gap with FAME, a dataset of 500 meetings in English and 300 in German produced by MIMIC, our new multi-agent meeting synthesis framework that generates…

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2024

MAGPIE: Multi-Task Analysis of Media-Bias Generalization with Pre-Trained Identification of Expressions

Tomáš Horych, Martin Paul Wessel, Jan Philip Wahle, Terry Ruas, Jerome Waßmuth, André Greiner-Petter +3

COLING 2024main

Media bias detection poses a complex, multifaceted problem traditionally tackled using single-task models and small in-domain datasets, consequently lacking generalizability. To address this, we introduce MAGPIE, a large-scale multi-task pre-training approach explicitly tailored for media bias detec…

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2024

Paraphrase Types Elicit Prompt Engineering Capabilities

Jan Philip Wahle, Terry Ruas, Yang Xu, Bela Gipp

EMNLP 2024main

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 expression of prompts affect these models. This study systematically and empirically evaluates which linguistic features i…

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2024

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

Frederic Kirstein, Jan Philip Wahle, Terry Ruas, Bela Gipp

EMNLP 2024finding

Meeting summarization has become a critical task considering the increase in online interactions. Despite new techniques being proposed regularly, the evaluation of meeting summarization techniques relies on metrics not tailored to capture meeting-specific errors, leading to ineffective assessment.…

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2023

Paraphrase Types for Generation and Detection

Jan Philip Wahle, Bela Gipp, Terry Ruas

EMNLP 2023long main

Current approaches in paraphrase generation and detection heavily rely on a single general similarity score, ignoring the intricate linguistic properties of language. This paper introduces two new tasks to address this shortcoming by considering paraphrase types - specific linguistic perturbations a…

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2023

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

Mohamed Abdalla, Jan Philip Wahle, Terry Ruas, Aurélie Névéol, Fanny Ducel, Saif Mohammad +1

ACL 2023long

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 one of the big players in the field of NLP, together with governments and universities, it is important to track the infl…

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2023

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

Jan Philip Wahle, Terry Ruas, Mohamed Abdalla, Bela Gipp, Saif M. Mohammad

EMNLP 2023long main

Natural Language Processing (NLP) is poised to substantially influence the world. However, significant progress comes hand-in-hand with substantial risks. Addressing them requires broad engagement with various fields of study. Yet, little empirical work examines the state of such engagement (past or…

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2022

How Large Language Models are Transforming Machine-Paraphrase Plagiarism

Jan Philip Wahle, Terry Ruas, Frederic Kirstein, Bela Gipp

EMNLP 2022main

The recent success of large language models for text generation poses a severe threat to academic integrity, as plagiarists can generate realistic paraphrases indistinguishable from original work.However, the role of large autoregressive models in generating machine-paraphrased plagiarism and their…

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