Explainable AI Berlin

@xai-berlin.bsky.social

Explainable AI research from the machine learning group of Prof. Klaus-Robert Müller at @tuberlin.bsky.social & @bifold.berlin

📣 Announcing the BlackboxNLP 2026 Reproducibility Challenge! A new track dedicated to rigorous robustness checks of NLP interpretability work - stress-testing baselines, ablations, generalizability, and evaluation.

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🔎 Today, we highlight a brand new paper, introducing a triad of open-source packages for dataset-wide and quantitative analyses of attributions. Attribution methods are powerful explanation tools, but by themselves cumbersome to generate dataset-wide insights. Not anymore!

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✈️🇲🇽 Next Wednesday (Dec 3), 1–4 p.m. CST, I’ll be presenting Manipulating Feature Visualizations with Gradient Slingshots at NeurIPS 2025 in Mexico City! Feature Visualization has long been a staple interpretability tool. Our work shows it’s far from reliable! 🚨

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Heading to the EMNLP BlackboxNLP Workshop this Sunday? Don’t miss @nfel.bsky.social and @lkopf.bsky.social poster on „Interpreting Language Models Through Concept Descriptions: A Survey“ aclanthology.org/2025.blackbo... #EMNLP #BlackboxNLP #XAI #Interpretapility

Nils Feldhus@nfel.bsky.social · 9mo ago

Nov 9, @blackboxnlp.bsky.social , 11:00-12:00 @ Hall C – Interpreting Language Models Through Concept Descriptions: A Survey (Feldhus & Kopf) @lkopf.bsky.social 🗞️ aclanthology.org/2025.blackbo... bsky.app/profile/nfel...