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Showing papers from Technische Universität Clausthal Show all papers

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NeurIPS 2026Clausthal University of TechnoloU MannheimRamblr GmbHTechnische Universität ClausthalExplainable AI

Concepts in Motion: Temporal Concept Bottleneck Model for Interpretable Video Classification

MoTIF uses a transformer over temporally grounded concept sequences with per-concept self-attention and automatic VLM concept discovery to improve interpretable video classification.

Patrick Knab, Sascha Marton, Philipp J Schubert, Drago A Guggiana Nilo and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · Code ★ 6

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lenient 4/5
medium 4/10
strict 1/5
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NeurIPS 2026U MannheimPrior LabsAWS AISiemens Corporate ResearchU RostockTabular data

TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks

TabPrep is a lightweight feature engineering pipeline that targets structural data patterns to consistently boost tabular model performance across benchmarks.

Andrej Tschalzev, Nick Erickson, Yuyang (Bernie) Wang, Huzefa Rangwala and 3 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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lenient 5/5
medium 8/10
strict 1/5
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NeurIPS 2026TU ClausthalTechnische Universität ClausthalAutoML & architecture search

Solver-Aware Decompositions for Programming-by-Example: When Dividing Requires Knowing how to Conquer

Solver-Aware Decomposition trains PBE decomposers via synthesizer feedback, showing ground-truth subgoal alignment does not improve synthesis and optimizing for solver tractability yields consistent accuracy gains.

Janis Zenkner, Tobias Sesterhenn, Tim Grams, Christian Bartelt

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 1/5