Florian Eichin

Semantic Component Analysis: Introducing Multi-Topic Distributions to Clustering-Based Topic Modeling Florian Eichin, Carolin M. Schuster, Georg Groh, Michael A. Hedderich. Findings of the Association for Computational Linguistics: EMNLP 2025. 2025.

Joining this interesting thread: Here's an idea using the embedding->clustering approach to id such dims (similar to SAEs) and how to use it for topic modeling and decomposing representations.
aclanthology.org/2025.finding...
(it's my Master's thesis, unaware of MechInterp and LRH etc.)

✨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 — producing e.g. Cyrillic Japanese transcriptions.

Thank you to our great Munich Center for Machine Learning (@munichcenterml.bsky.social) for featuring me in this research film! Lots of great films clips with my MCML colleagues are available on MCML's YouTube channel. #ai #aiethics #mcml #philosophy youtu.be/KUqiY8o1yng?...

Unsure which presentations to attend at #ACL2025? 🛎️🗣️

🕺🏼swing by our poster in Hall 4/5 on Wednesday, July 30 at 11:00 to chat with @florian-eichin.com and I to find out the answers to these questions

🛎️ bonus: to see the full poster 🫣🧩

#ACL2025 #NLProc

is the bike doing fine though?? 😥

📝Probing LLMs for Multilingual Discourse Generalization Through a Unified Label Set
🔎Do LLMs encode and generalize discourse knowledge across languages?
👥 @florian-eichin.com @janetlauyeung.bsky.social @mhedderich.bsky.social @barbaraplank.bsky.social
🔗 arxiv.org/abs/2503.10515
📁Main - Long

Some recommendations for #ACL2025 👇
(join me and @janetlauyeung.bsky.social to talk about discourse generalization and probing!)

Headed to ACL? MaiNLP & our most recent work will be there too👥📄
Come see what we’ve been working on!

XAI’s dogwater performance on the 2025 IMO confirms that their Grok 4 benchmark claims were hot air. Their eye popping metrics were down to the following innovations:
- train on test
- train on test
- train on test

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

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

Interpretability meets Discourse. Congratulations to
@florian-eichin.com to his first ACL paper 🎉

Paper alert 🛎️

to appear at ACL2025

🦙 how well do LLMs encode discourse knowledge? does that generalize across languages?

🛎️ in our #ACL2025 paper, we uncover fascinating trends about multilingual discourse representations!

joint work w/ @florian-eichin.com @barbaraplank.bsky.social @mhedderich.bsky.social

📄 arxiv.org/abs/2503.10515

I’ll be at @icmlconf.bsky.social next week presenting NoLiMa!
Poster on Tue July 15, 4:30–7pm (E-2312).

Happy to grab a coffee and chat about long-context, memory, research, or just to catch up.

I’ll be in Toronto for a couple of days after the conference, let me know if you’re around!

Caught some great moments at #MCML Munich AI Day 2025 last week📍
From sharp keynotes to poster debates. Our team had the chance to show some recent work, join the conversations, and bring back plenty of food for thought🧠🗣️📊

The study is here but gated: journals.sagepub.com/doi/10.3102/...

I’d be curious how these dynamics play out in our NLP review crisis. My hunch: many conscientious volunteers might be junior women. That time comes at a cost; chasing slackers means less time for rebutting my own reviews.

Thanks for the invitation to the Freiburg Institute for Advanced Studies (FRIAS) to give this year's Hermann-Paul-Center Lecture lnkd.in/d_wUeDfY

I enjoyed the visit, the great audience, and the stay in this lovely city.
Thank you
#blackforest #freiburg #breisgau

preprint is out

bsky.app/profile/alex...

My MSc-thesis has been turned into a paper (whose framing you will probably not enjoy) that introduces a method which can be viewed as an unsupervised solution to a similar problem. Will share later to avoid biasing review process

Interesting! And indeed very relevant as it enables control over the similarity modeled by the embeddings. Figure 2 is really cool. Which base embeddings were used for this?

Haha can't wait. Let's continue the discussion at ACL!

Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of Topic Models A common use of NLP is to facilitate the understanding of large document collections, with a shift from using traditional topic models to Large Language Models. Yet the effectiveness of using LLM for ...

Also, I remember your other ACL 2025 paper which shows that the LLM approach comes with problems for topic quality, too? Very interesting read arxiv.org/abs/2502.14748

Yeah, agreed and aware of your work :) though as established above, emb+clustering has its niche in large scale analysis with factors like multilinguality. There, LDA tends to have problems and TopicGPT is too expensive.

Awesome! And yes, I totally understand and agree with the scepticism towards that

Mixed language data is common on, e.g., Chinese Twitter which we found to be very diverse. Since topics are distributions over tokens and a single doc is usually just one language, the only way I see to make LDA work is by translating Tweets?

Yeah, that makes a lot of sense. I think of BERTopic as a convenient, quick way to try that on your own data, which is, I think, another reason why less techy people like to use it.

What scenarios are you 'typically' considering? Working with Twitter data of 1M+ samples, I couldn't get any of the LDA derivates I've tried to produce good results. Non-English/mixed language data is also challenging. (Genuinely curious)