Ece Takmaz

Ece Takmaz

@ecekt.bsky.social

Interim Professor for AI and Computational Linguistics at LMU Munich Previously Postdoc at Utrecht University, PhD candidate at the University of Amsterdam Multimodal NLP, Vision and Language, Cognitively Inspired NLP https://ecekt.github.io/

643 followers529 following61 posts

Computational Psycholinguistics Meeting (CPL 2026) has an updated submission deadline! (July 17) ☀️

Ece Takmaz@ecekt.bsky.social

After the very nice 15th edition of CMCL last Saturday 🌴, I'm happy to announce that the 2nd edition of the Computational Psycholinguistics Meeting (CPL 2026) will take place again in Utrecht in December! We are looking forward to receiving abstracts ✨ cpl2026.sites.uu.nl

MINT deadline extended to July 22nd!

Ece Takmaz@ecekt.bsky.social

🍃2nd Call for Papers!😊 EMNLP 2026 Workshop on Multimodal Interaction in Face-to-Face Dialogue (MINT) welcomes work on multimodal communication, speech, gesture, gaze, facial expressions, datasets, eval methods, and applications! @emnlpmeeting.bsky.social mintworkshop.github.io

CMCL deadline extended to Feb 28 AoE!

Ece Takmaz@ecekt.bsky.social

The submission deadline for CMCL is coming up in less than a month! (Feb 25) CMCL will be co-located with LREC and take place on May 16!🌴https://sites.google.com/view/cmclworkshop/cfp

The submission deadline for CMCL is coming up in less than a month! (Feb 25) CMCL will be co-located with LREC and take place on May 16!🌴https://sites.google.com/view/cmclworkshop/cfp

Ece Takmaz@ecekt.bsky.social

Cognitive Modeling and Computational Linguistics (CMCL) workshop will be co-located with LREC 2026 in Palma, Mallorca!🌴Stay tuned for more details!✨ @byungdoh.bsky.social Tatsuki Kuribayashi @grambelli.bsky.social Philipp Wicke, Jixing Li, Ryo Yoshida @cmclworkshop.bsky.social

The CfP for CMCL is out!🌴 We are looking forward to receiving many interesting submissions! ✨ (Deadline: February 25, 2026) sites.google.com/view/cmclwor...

scholar.google.comscholar.google.com
Ece Takmaz@ecekt.bsky.social

Cognitive Modeling and Computational Linguistics (CMCL) workshop will be co-located with LREC 2026 in Palma, Mallorca!🌴Stay tuned for more details!✨ @byungdoh.bsky.social Tatsuki Kuribayashi @grambelli.bsky.social Philipp Wicke, Jixing Li, Ryo Yoshida @cmclworkshop.bsky.social

Many thanks to @dnliu.bsky.social for inviting me, and to the members of the group for their insightful questions! 😊✨

AI4LT@ai4lt.bsky.social

Last week @ecekt.bsky.social gave a great talk on her recent work "Model Merging to Maintain Language-Only Performance in Developmentally Plausible Multimodal Models"! Thank you so much for joining us, Ece! 🌟

I was in Sweden this week! 🇸🇪❄️ Many thanks to Nikolai Ilinykh for inviting me to give a talk at the University of Gothenburg. I enjoyed having inspiring chats and delicious food with Sharid Loáiciga, @asayeed.bsky.social, Simon Dobnik, Hyewon Jang and Chris Howes at CLASP. Much appreciated! 😊🎄

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Instead of using the data provided in the BabyLM challenge, I opted for obtaining them from their sources, which added extra layers of filtering and complexity, revealing some discrepancies in the multimodal BabyLM data. I mention these in the paper.

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The report on the Findings of the Third BabyLM Challenge indicates that the multimodal track received only 1 full submission this year. We submitted our paper to the workshop track instead of the challenge.

Unfortunately, we had limited time and resources to modify the whole evaluation pipeline for our specific multimodal architecture. As a result, we tested our models on a subset of the benchmarks.

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How can we mitigate this issue in developmentally plausible multimodal models and maintain language-only performance? We explored model merging, a technique that has been shown to benefit multi-task and multi-language models, reducing the effects of catastrophic forgetting.

We experiment with weighted linear interpolation of language-only and multimodal model weights. Model merging with language-only checkpoints helps alleviate the issue to some extent, benefiting performance in language-only benchmarks and not disrupting accuracy in multimodal tasks heavily.

Previous work, including BabyLM contributions, indicates that multimodal data has limited or no benefits in text-only benchmarks. We reach similar conclusions in our low-resource multimodal scenario.

Our multimodal BabyLM model surpasses previous multimodal baselines and submissions on the leaderboard. Yet, compared to language-only models, it underperforms in grammar-oriented benchmarks, although being exposed to the same language-only data as the language-only models (+ multimodal data).

Just got back from Hawaii, where I presented a workshop paper on image memorability at @iccv.bsky.social 🌺 Coming from multimodal NLP, it was my first time attending a CV conference. Everywhere I looked, there were talks and posters that were incredibly interesting!

Ece Takmaz reposted

🌍Introducing BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data! LLMs learn from vastly more data than humans ever experience. BabyLM challenges this paradigm by focusing on developmentally plausible data We extend this effort to 45 new languages!

What makes an image memorable? And can we predict image memorability using pretrained vision encoders? We explored activations, attention distributions, image patch uniformity and sparse autoencoder losses using image representations across the layers of CLIP, DINOv2 and SigLIP2.

Ece Takmaz reposted

Had such a great time presenting our tutorial on Interpretability Techniques for Speech Models at #Interspeech2025! 🔍 For anyone looking for an introduction to the topic, we've now uploaded all materials to the website: interpretingdl.github.io/speech-inter...

interpretingdl.github.ioInterpretability Techniques for Speech Models — Tutorial @ Interspeech 2025
Grzegorz Chrupała@grzegorz.chrupala.me

And that's the whole team behind the tutorial on interpretability techniques for speech models at IS2025.