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MaiNLP lab, LMU Munich

@mainlp.bsky.social

MaiNLP research lab at CIS, LMU Munich directed by Barbara Plank @barbaraplank.bsky.social Natural Language Processing | Artificial Intelligence | Computational Linguistics | Human-centric NLP

196 Followers  |  70 Following  |  25 Posts  |  Joined: 22.01.2025  |  2.1257

Latest posts by mainlp.bsky.social on Bluesky

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✨New paper✨

We find script (e.g. Cyrillic, Latin) to be a linear direction in the activation space of Whisper, enabling transliteration at test-time by adding such script directions to the activations β€” producing e.g. Cyrillic Japanese transcriptions.

07.01.2026 03:04 β€” πŸ‘ 9    πŸ” 4    πŸ’¬ 1    πŸ“Œ 0
VarDial @ EACL 2026, with important dates (see next post for text version). 
Photo CC-0.

VarDial @ EACL 2026, with important dates (see next post for text version). Photo CC-0.

VarDial 2026 will be colocated with @eaclmeeting.bsky.social! We're looking forward to your papers on NLP for similar languages, varieties and dialects :)

Deadline: Dec 19 (Jan 2 for pre-reviewed ARR papers)
sites.google.com/view/vardial...

21.10.2025 10:36 β€” πŸ‘ 14    πŸ” 10    πŸ’¬ 1    πŸ“Œ 0
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Group photo at NeurIPS 2025 San Diego

07.12.2025 18:40 β€” πŸ‘ 9    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

Congrats to Pingjun, @beiduo.bsky.social , Siyao, Marie, and @barbaraplank.bsky.social for receiving the SAC Highlights reward!

13.11.2025 18:02 β€” πŸ‘ 5    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

Congrats to our team member Diego Frassinelli on the SAC Highlights award!

13.11.2025 17:59 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Awesome! We're also creating one currently and have included yours as a starter :)

11.08.2025 12:19 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
Piper title ("A multi-dialectal dataset for German dialect ASR and dialect-to-standard speech translation") and a map of the German state Bavaria showing where the Franconian, Bavarian, and Alemannic dialect groups are spoken

Piper title ("A multi-dialectal dataset for German dialect ASR and dialect-to-standard speech translation") and a map of the German state Bavaria showing where the Franconian, Bavarian, and Alemannic dialect groups are spoken

At #Interspeech2025 I'm going to present Betthupferl, a dataset for German dialect ASR & dialect-to-standard speech translation! We analyze differences between dialectal & Standard German transcriptions, benchmark ASR models, and examine shortcomings of current ASR models & evaluation metrics.

07.08.2025 08:46 β€” πŸ‘ 16    πŸ” 4    πŸ’¬ 1    πŸ“Œ 1

UPDATE: Our poster presentation got moved to Tuesday, 16:00–17:30 (session 10)! #ACL2025NLP

27.07.2025 14:39 β€” πŸ‘ 3    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

Unsure which presentations to attend at #ACL2025? πŸ›ŽοΈπŸ—£οΈ

27.07.2025 09:56 β€” πŸ‘ 4    πŸ” 2    πŸ’¬ 0    πŸ“Œ 0

πŸ‘₯β€ͺ @boleima.bsky.social Yuting Li, Wei Zhou, Ziwei Gong, @janetlauyeung.bsky.social Katja Jasinskaja @annefriedrich.bsky.social Julia Hirschberg, Frauke Kreuter @barbaraplank.bsky.social

23.07.2025 12:32 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

πŸ‘₯β€ͺ @boleima.bsky.social Berk Yoztyurk @carohaensch.bsky.social @xinpeng.bsky.social Markus Herklotz, Frauke Kreuter @barbaraplank.bsky.social @assenmacher.bsky.social

23.07.2025 12:31 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

πŸ“ Analyzing the Effect of Linguistic Similarity on Cross-Lingual Transfer: Tasks and Experimental Setups Matter
πŸ”Ž 263 languages, 10 similarity measures, 3 NLP tasks
πŸ‘₯ @verenablaschke.bsky.socialΒ Masha Fedzechkina @maartjeterhoeve.bsky.social
πŸ”— arxiv.org/abs/2501.14491
πŸ“ Findings – long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

πŸ“Do LLMs Give Psychometrically Plausible Responses in Educational Assessments?
πŸ”ŽAnalyzing how human-like LLMs are when taking reading, history, and economics tests
πŸ‘₯ @saeub.bsky.social , Diego Frassinelli, @barbaraplank.bsky.social
πŸ”— arxiv.org/abs/2506.09796
πŸ“BEA workshop - Long

23.07.2025 12:29 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

πŸ“ GerMedIQ: A Resource for Simulated and Synthesized Anamnesis Interview Responses in German
πŸ”Ž We release a novel German anamnesis question-response dataset with human-simulated and LLM-augmented responses.
πŸ‘₯ @JHofenbitzer et al.
πŸ”— github.com/Jhofenbitzer...
πŸ“SRW - Long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

πŸ“Probing LLMs for Multilingual Discourse Generalization Through a Unified Label Set
πŸ”ŽDo LLMs encode and generalize discourse knowledge across languages?
πŸ‘₯ @florian-eichin.com @janetlauyeung.bsky.social @mhedderich.bsky.social @barbaraplank.bsky.social
πŸ”— arxiv.org/abs/2503.10515
πŸ“Main - Long

23.07.2025 12:29 β€” πŸ‘ 3    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1

πŸ“LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks
πŸ”ŽWe present a large-scale study of whether LLM judgments can be reliably used as proxies for human judgments
πŸ‘₯Anna Bavaresco et al.
πŸ”— arxiv.org/abs/2406.18403
πŸ“Main - Short

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

πŸ“ What's the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token Patterns
πŸ‘₯ @mhedderich.bsky.social Anyi Wang @raoyuan.bsky.social @florian-eichin.com Jonas Fischer @barbaraplank.bsky.social 

πŸ”— arxiv.org/abs/2504.158...

πŸ“Main - Long

23.07.2025 12:29 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

πŸ“A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI
πŸ‘₯ @beiduo.bsky.social Siyao Peng @annakorhonen.bsky.social @barbaraplank.bsky.social
πŸ”— arxiv.org/abs/2412.13942
πŸ“ACL25 Findings-Long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

πŸ“Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models
πŸ”ŽWe study the relationship between circuits for highly compositional and functionally related tasks
πŸ‘₯@pmondorf.bsky.social Sondre Wold @barbaraplank.bsky.social
πŸ”— arxiv.org/abs/2410.01434
πŸ“Main-Long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

πŸ“Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
πŸ”ŽWe review existing datasets for evaluating LLMs’ pragmatic capabilities, outlining key challenges and promising future directions
πŸ”— arxiv.org/abs/2502.12378
πŸ“Main - Long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 2    πŸ“Œ 0

πŸ“Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study
πŸ”ŽThis study evaluates LLMs in generating German public opinions using open-ended survey data
πŸ”— arxiv.org/abs/2412.13169
πŸ“Main - Long

23.07.2025 12:29 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 2    πŸ“Œ 0
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Headed to ACL? MaiNLP & our most recent work will be there tooπŸ‘₯πŸ“„
Come see what we’ve been working on!

23.07.2025 12:29 β€” πŸ‘ 14    πŸ” 5    πŸ’¬ 1    πŸ“Œ 2
Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models A fundamental question in interpretability research is to what extent neural networks, particularly language models, implement reusable functions through subnetworks that can be composed to perform mo...

πŸ“„Β [ACL 2025 main] Circuit compositions: Exploring Modular Structures in Transformer-Based Language Models (doi.org/10.48550/arX...)

18.07.2025 10:19 β€” πŸ‘ 5    πŸ” 2    πŸ’¬ 1    πŸ“Œ 0
LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks There is an increasing trend towards evaluating NLP models with LLMs instead of human judgments, raising questions about the validity of these evaluations, as well as their reproducibility in the case...

πŸ“„Β [ACL 2025 main] LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks (doi.org/10.48550/arX...)

18.07.2025 10:19 β€” πŸ‘ 10    πŸ” 4    πŸ’¬ 1    πŸ“Œ 0
Correlations between transfer results per experiment (parsing, POS tagging, topic classification with different input representations) and similarity measures. The results vary a lot across experiments and measures – some are described in the next posts.

Correlations between transfer results per experiment (parsing, POS tagging, topic classification with different input representations) and similarity measures. The results vary a lot across experiments and measures – some are described in the next posts.

At #ACL2025NLP I'll present our analysis of the effect of linguistic similarity on cross-lingual transfer! We looked at how 10 similarity measures correlate w/ transfer results btwn 263 languages across 3 NLP tasks. Different similarity measures matter for diff. experiments (no one-size-fits-all)!

18.07.2025 10:43 β€” πŸ‘ 21    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1
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πŸ€” Can LLMs read between the lines?

Our another #ACL2025 paper surveys resources on how LLMs handle pragmatics like implicatures, deixis, and more. We map out a new landscape for both LLMs and linguistics in pragmatic research.

πŸ“„ arxiv.org/abs/2502.12378
πŸ§ πŸ’¬ #LLMs #Pragmatics

16.07.2025 09:42 β€” πŸ‘ 16    πŸ” 4    πŸ’¬ 1    πŸ“Œ 1
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🚨 Can LLMs generate explanations that are as useful as human ones for modeling label distributions in NLI?🌹"A Rose by Any Other Name" shows that they can
πŸ’¬ We explore scalable, explanation-based annotation via LLMs.
πŸ“Come find us in Vienna πŸ‡¦πŸ‡Ή! (July 28, 18:00-19:30, Hall 4/5) #ACL2025NLP #acl2025

15.07.2025 14:46 β€” πŸ‘ 5    πŸ” 1    πŸ’¬ 3    πŸ“Œ 0
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πŸŽ‰ Our paper β€œAlgorithmic Fidelity of LLMs in Generating Synthetic German Public Opinions” is accepted at #ACL2025 main conference as an oral presentation! πŸ‡©πŸ‡ͺπŸ€–

We study how well LLMs simulate real survey responses using open-ended German data, showing the left-leaning bias.

14.07.2025 14:32 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1

The future of AI literacy starts early! Our very own @fkoerner.bsky.social recently led a series of hands-on workshops teaching some of our youngest students yet πŸŒ±πŸ€–

11.07.2025 13:57 β€” πŸ‘ 3    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Looking forward to my visit to Hamburg University and their Data Science group!

11.07.2025 11:06 β€” πŸ‘ 3    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

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