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Grzegorz Chrupała

@grzegorz.chrupala.me

Speech • Language • Learning https://grzegorz.chrupala.me @ Tilburg University

121 Posts3333 Follower1003 Folgt
Laurens@laurenshof.online · 4w ago

reading through the actual plan now, and it is hard to overstate how incredible funny and insane it is to say "we are gonna threaten you with a fine of 3% of global revenue if you share your most powerful technology with us"

2.1. Assessing and mitigating risks posed by frontier AI The AI Act sets out requirements for the cybersecurity of AI systems14 and requires providers of the most advanced general-purpose AI models to assess and mitigate systemic risks, including from misuse of AI in the cyber domain.15 As of 2 August 2026, the Commission will exercise the supervisory and enforcement powers provided by the AI Act to ensure effective oversight of AI systems as well as of general-purpose AI models, including models that present systemic risks related to cybersecurity.16 This oversight includes assessing the providers’ identification of risks associated with model capabilities and their implemented measures to mitigate those risks. These requirements continue to be proportionate to the capabilities of the technology at hand. The supervisory and enforcement powers will be supported by the Scientific Panel advising the Commission’s AI Office, secure reporting channels, and the Code of Practice for general-purpose AI.
Carl Zimmer@carlzimmer.com · last mo.

Meet SpudCell, a synthetic cell made from lifeless ingredients that feeds, grows, divides, and experiences selection. If it doesn't have all the hallmarks of life, it has a lot! Here's my story. Gift link: nyti.ms/4vCbTih

A series of images of a dividing synthetic cell
hardmaru@hardmaru.bsky.social · 2mo ago

Human intelligence is fundamentally a collective intelligence. We solve complex problems by participating in a vast cultural network that builds upon ideas across generations. I believe the strongest AI systems will become a collective intelligence, too.

Sakana AI@sakanaai.bsky.social · 2mo ago

Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API. Our ‘Fugu Ultra’ model matches the performance of Fable and Mythos, delivering frontier capability without the risk of export controls. Try it: sakana.ai/fugu 🐡

Erik Bekkers@erikjbekkers.bsky.social · 4mo ago

We're looking for a new colleague at @amlab.bsky.social: Assistant Professor in AI for Science 🔬🤖 World-class ML research, Amsterdam's thriving AI ecosystem (ELLIS, startups, big tech), and some of the best academic labor conditions in Europe ❤️ Deadline: May 30 👉 werkenbij.uva.nl/en/vacancies...

Vacancy — Assistant Professor in AI for Science (AI4Science)

<p><span>Are you passionate about advancing Machine Learning by integrating insights from the natural sciences? Are you eager to bridge the 3rd (<em><span>computational</span></em>) and 4th (<em><span...

werkenbij.uva.nl

Laurent Besacier@lbesacier.bsky.social · 4mo ago

🚀 #ALPS2026 is officially open in the French Alps! A unique winter school combining cutting-edge NLP research with an exceptional setting for collaboration and exchange: 🔹 55 participants from around the world 🔹 77% PhD students 🔹 7 international speakers from Canada, Denmark, France, and the UK

Bild
@evavnmssnhv.bsky.social · 5mo ago

Proud of @chiaramanna.bsky.social and Argentina Anna Rescigno who had their papers accepted at #LREC2026: 👏Manna et al.: on gender bias in decoder-only arxiv.org/abs/2603.17952 👏Rescigno et al.: on ConGA - a framework for contextual gender annotation in MT arxiv.org/abs/2603.17962

Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures

While Large Language Models achieve state-of-the-art results across a wide range of NLP tasks, they remain prone to systematic biases. Among these, gender bias is particularly salient in MT, due to sy...

arxiv.org

Gabriele Sarti@gsarti.com · 5mo ago

BlackboxNLP is back once again at EMNLP'26! Very happy to be part of the team again, and excited for our new reproducibility track! Check it out ⬇️

BlackboxNLP@blackboxnlp.bsky.social · 5mo ago

BlackboxNLP will be co-located with EMNLP 2026 in 🇭🇺 Budapest 🇭🇺 this October! This edition will feature a special reproducibility track, investigating generalization and robustness of established results from interpretability research 👷‍♂️ Stay tuned for more details!

Marianne de Heer Kloots@mdhk.net · 8mo ago

'Tis the season to preprint BBS commentaries; I'm happy to share ours too! 🎄✨ The textual basis of current LLMs causes trouble, but linguistically relevant insights *can* be found in systems modelling the more natural form of human spoken language: the speech signal itself. arxiv.org/abs/2512.14506

Commentary title: Linguists should learn to love speech-based deep learning models Authors: Marianne de Heer Kloots, Paul Boersma, Willem Zuidema Abstract: Futrell and Mahowald present a useful framework bridging technology-oriented deep learning systems and explanation-oriented linguistic theories. Unfortunately, the target article's focus on generative text-based LLMs fundamentally limits fruitful interactions with linguistics, as many interesting questions on human language fall outside what is captured by written text. We argue that audio-based deep learning models can and should play a crucial role.
Marianne de Heer Kloots@mdhk.net · 12mo ago

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...

Interpretability Techniques for Speech Models — Tutorial @ Interspeech 2025

interpretingdl.github.io

Grzegorz Chrupała@grzegorz.chrupala.me · 12mo ago

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

Left to right Charlotte Pouw, Willem Zuidema, Marianne de Heer Kloots, Martijn Bentum, Hosein Mohebbi, Grzegorz Chrupała, Gaofei Shen & Tom Lentz.