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20232026
most citedVoting or Consensus? Decision-Making in Multi-Agent Debate

13 citations · 65 across the 39 of their papers we have counts for

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13 papers · 1 filter

cs.DL2025

Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias

Max Martin Gnewuch, Jan Philip Wahle, Terry Ruas +1

Over the past four decades, artificial intelligence (AI) research has flourished at the nexus of academia and industry. However, Big Tech companies have increasingly acquired the e…

cs.AI2025

ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents

Tianyu Yang, Terry Ruas, Yijun Tian +3

Vision-language models (VLMs) excel at interpreting text-rich images but struggle with long, visually complex documents that demand analysis and integration of information spread a…

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★ 1 cited

Re-FRAME the Meeting Summarization SCOPE: Fact-Based Summarization and Personalization via Questions

Frederic Kirstein, Sonu Kumar, Terry Ruas +1

Meeting summarization with large language models (LLMs) remains error-prone, often producing outputs with hallucinations, omissions, and irrelevancies. We present FRAME, a modular…

cs.MA2025

MALLM: Multi-Agent Large Language Models Framework

Jonas Becker, Lars Benedikt Kaesberg, Niklas Bauer +3

Multi-agent debate (MAD) has demonstrated the ability to augment collective intelligence by scaling test-time compute and leveraging expertise. Current frameworks for multi-agent d…

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.AI2025

SPaRC: A Spatial Pathfinding Reasoning Challenge

Lars Benedikt Kaesberg, Jan Philip Wahle, Terry Ruas +1

Existing reasoning datasets saturate and fail to test abstract, multi-step problems, especially pathfinding and complex rule constraint satisfaction. We introduce SPaRC (Spatial 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

Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language

Anastasia Zhukova, Christian E. Matt, Bela Gipp

Domain-adaptive continual pretraining (DAPT) is a state-of-the-art technique that further trains a language model (LM) on its pretraining task, e.g., masked language modeling (MLM)…

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.MA2025★ 13 cited

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

Lars Benedikt Kaesberg, Jonas Becker, Jan Philip Wahle +2

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,…

cs.AI2025

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

Frederic Kirstein, Muneeb Khan, Jan Philip Wahle +2

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…

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…