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Showing papers from Karlsruhe Institute of Technology (KIT) Show all papers

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NeurIPS 2026Karlsruher Institut für TechnoloKarlsruhe Institute of TechnologKarlsruhe Institute of TechnologFZI Research Center for InformatUniversidad Carlos III de MadridDatasets & benchmarks

The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset

KITScenes Multimodal provides European autonomous driving data with high-fidelity synchronized sensors, complete topologically connected 3D HD maps, and four embodied AI benchmarks.

Richard Schwarzkopf, Fabian Immel, Alexander Blumberg, Jonas Merkert and 20 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 19 on Hugging Face · Code ★ 26

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NeurIPS 2026Karlsruhe Institute of TechnologNational University of SingaporeFraunhofer IOSBU BonnKarlsruhe Institute of TechnologTest-time compute

Rethinking Expressivity and Efficiency in Test-Time Training

E²-TTT derives a closed-form chunk-level state transition that exactly reproduces per-token update dynamics, enabling parallel training that retains temporal structure, matches chunk-wise throughput, and achieves over 90% needle-in-a-haystack accuracy at 8× training length.

Zeyun Zhong, Joya Chen, Manuel Martin, Frederik Diederichs and 2 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 2 on Hugging Face · Code ★ 4

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medium 9/10
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NeurIPS 2026KIT - Karlsruhe Institute of TecKarlsruher Institut für TechnoloAleph Alpha ResearchKarlsruhe Institute of TechnologKarlsruhe Institute of TechnologPhysics-informed ML & PDEs

Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators

PEACH adapts graph network simulators via point cloud sequence encoding for in-context material inference, achieving accurate zero-shot sim-to-real transfer and outperforming mesh-based baselines.

Philipp Dahlinger, Balázs Gyenes, Niklas Freymuth, Luca Geminiani and 5 more

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

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AI panel: 10 of 20 reviewers recommend it
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medium 5/10
strict 0/5