Jan Philip Wahle

Orcid: 0000-0002-2116-9767

Affiliations:
  • University of Göttingen, Germany
  • University of Wuppertal, Germany (former)


According to our database1, Jan Philip Wahle authored at least 53 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling.
CoRR, May, 2026

Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains.
CoRR, April, 2026

Mind the Gap Between Spatial Reasoning and Acting! Step-by-Step Evaluation of Agents With Spatial-Gym.
CoRR, April, 2026

SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA).
CoRR, April, 2026

Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification.
CoRR, March, 2026

Language Modeling and Understanding Through Paraphrase Generation and Detection.
CoRR, February, 2026

DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysis.
CoRR, January, 2026

DimStance: Multilingual Datasets for Dimensional Stance Analysis.
CoRR, January, 2026

Stay Focused: Problem Drift in Multi-Agent Debate.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysis.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science.
CoRR, December, 2025

Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias.
CoRR, December, 2025

Language Modeling and Understanding Through Paraphrase Generation and Detection.
PhD thesis, 2025

CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization.
J. Artif. Intell. Res., 2025


CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization (Abstract Reprint).
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

The Language of Interoception: Examining Embodiment and Emotion Through a Corpus of Body Part Mentions.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

TrojanStego: Your Language Model Can Secretly Be A Steganographic Privacy Leaking Agent.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

SPaRC: A Spatial Pathfinding Reasoning Challenge.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

MALLM: Multi-Agent Large Language Models Framework.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Towards Human Understanding of Paraphrase Types in Large Language Models.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Overview of the Plagiarism Detection Task at PAN 2025.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum, 2025


You need to MIMIC to get FAME: Solving Meeting Transcript Scarcity with Multi-Agent Conversations.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Voting or Consensus? Decision-Making in Multi-Agent Debate.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
CiteAssist: A System for Automated Preprint Citation and BibTeX Generation.
CoRR, 2024

Towards Human Understanding of Paraphrase Types in ChatGPT.
CoRR, 2024

Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges.
CoRR, 2024

MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressions.
CoRR, 2024

Citation Amnesia: NLP and Other Academic Fields Are in a Citation Age Recession.
CoRR, 2024

Paraphrase Types Elicit Prompt Engineering Capabilities.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

What's under the hood: Investigating Automatic Metrics on Meeting Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Text-Guided Image Clustering.
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

MAGPIE: Multi-Task Analysis of Media-Bias Generalization with Pre-Trained Identification of Expressions.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
Paraphrase Detection: Human vs. Machine Content.
CoRR, 2023

A Cohesive Distillation Architecture for Neural Language Models.
CoRR, 2023

AI Usage Cards: Responsibly Reporting AI-Generated Content.
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2023

We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Paraphrase Types for Generation and Detection.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Research.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Analyzing Multi-Task Learning for Abstractive Text Summarization.
CoRR, 2022

CS-Insights: A System for Analyzing Computer Science Research.
CoRR, 2022

How Large Language Models are Transforming Machine-Paraphrased Plagiarism.
CoRR, 2022

D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Identifying Machine-Paraphrased Plagiarism.
Proceedings of the Information for a Better World: Shaping the Global Future - 17th International Conference, iConference 2022, Virtual Event, February 28, 2022

Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection.
Proceedings of the Information for a Better World: Shaping the Global Future - 17th International Conference, iConference 2022, Virtual Event, February 28, 2022

How Large Language Models are Transforming Machine-Paraphrase Plagiarism.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection.
Dataset, March, 2021

Identifying Machine-Paraphrased Plagiarism.
Dataset, January, 2021

Incorporating Word Sense Disambiguation in Neural Language Models.
CoRR, 2021

Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection.
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2021


  Loading...