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Showing papers from ELLIS Institute Tübingen / Max Planck Institute for Intelligent Systems Show all papers

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NeurIPS 2026OralMax Planck Institute for IntelliETH ZurichETH Zurich / Max Planck InstitutGoogle DeepmindETH ZürichLLM pretraining & scaling laws

LittleLearner: Language Models Under Pedagogically-Controlled Knowledge Exposure

LittleLearner is a 5B-parameter model trained on grade-capped elementary data to study controlled knowledge acquisition and bounded capability growth.

Fanfei Li, Jana Zeller, Manuel Prada-Corral, Thaddäus Wiedemer and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
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NeurIPS 2026EPFLSwiss Federal Institute of TechnMilaELLIS Institute Tübingen / Max PTest-time compute

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping

Learned stochastic stopping reduces out-of-distribution variance in looped transformers by decoupling loop count from sequence length during training. It improves accuracy-stability trade-offs across algorithmic tasks, though it can stabilize suboptimal computation.

Hsun-Yu Kuo, El Mahdi Chayti, Patrik Reizinger, Wieland Brendel and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 2/5