Research Group Jana Diesner
Jana Diesner
leads the Human-Centered Computing group at TU Munich.
Her interdisciplinary group works on methods from network analysis, natural language processing, machine learning and AI, and integrates them with theories from the social sciences and humanities to advance knowledge about socio-technical systems and responsible computing. Jana earned her Ph.D. at Carnegie Mellon and joined TUM from the University of Illinois Urbana Champaign, where she was a tenured professor at the School of Information Sciences.
Team members @MCML
PostDocs
PhD Students
Recent News @MCML
Publications @MCML
2026
[6]
S. Kolli • T. Cavelius • N. Nikeghbal • S. Dalal • J. Diesner
StylisticBias: A Few Human Visual Cues Drive Most Social Bias in MLLMs.
AI4GOOD @ICML 2026 - Workshop on Trustworthy AI for Good at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
StylisticBias: A Few Human Visual Cues Drive Most Social Bias in MLLMs.
AI4GOOD @ICML 2026 - Workshop on Trustworthy AI for Good at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
[5]
N. Nikeghbal • A. H. Kargaran • S. Kolli • J. Diesner
Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs.
AI4GOOD @ICML 2026 - Workshop on Trustworthy AI for Good at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs.
AI4GOOD @ICML 2026 - Workshop on Trustworthy AI for Good at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
[4]
N. Nikeghbal • A. H. Kargaran • S. Kolli • J. Diesner
Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs.
AIWILD @ICML 2026 - 2nd Workshop on Agents in the Wild: Safety, Security, and Beyond at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs.
AIWILD @ICML 2026 - 2nd Workshop on Agents in the Wild: Safety, Security, and Beyond at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
[3]
A. H. Kargaran • N. Nikeghbal • J. Diesner • F. Yvon • H. Schütze
GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts.
Preprint (Apr. 2026). arXiv GitHub
GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts.
Preprint (Apr. 2026). arXiv GitHub
2025
[2]
N. Nikeghbal • A. H. Kargaran • J. Diesner
CoBia: Constructed Conversations Can Trigger Otherwise Concealed Societal Biases in LLMs.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub
CoBia: Constructed Conversations Can Trigger Otherwise Concealed Societal Biases in LLMs.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub
[1]
A. H. Kargaran • A. Modarressi • N. Nikeghbal • J. Diesner • F. Yvon • H. Schütze
MEXA: Multilingual Evaluation of English-Centric LLMs via Cross-Lingual Alignment.
Findings @ACL 2025 - Findings at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI
MEXA: Multilingual Evaluation of English-Centric LLMs via Cross-Lingual Alignment.
Findings @ACL 2025 - Findings at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI
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2025-10-06 - Last modified: 2026-07-03