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Showing papers from Ghent University Show all papers

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Efficient Test-Time Adaptation For Robot Policies

Motasem Alfarra, Pietro Mazzaglia, Markus Peschl, Daniel Dijkman 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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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
45%Niche pick
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SO(3)-Equivariant Learning on CAD Boundary Representations

Matteo Ballegeer, Dries Benoit

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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83%Must read
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Towards Error-Free EHRs: Reasoning-Intensive Consistency Verification Between Clinical Notes and Structured Tables in Electronic Health Records

EHR-ReasonCon introduces a reasoning-intensive benchmark for clinical note-table consistency verification, and EHR-Inspector achieves state-of-the-art results via LLM-based verification with table exploration.

Yeonsu Kwon, Jiho Kim, Junseong Choi, Paloma Rabaey and 9 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 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 5/5
medium 7/10
strict 1/5
83%Must read
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Membership Inference on Synthetic Single-Cell Genomic Data

Membership inference attacks successfully identify training donors in synthetic single-cell RNA-seq data, revealing that leading generation methods inadequately protect privacy and leak more as donor counts drop.

Steven Golob, Patrick McKeever, Sikha Pentyala, Martine De Cock and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
83%Must read
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LARGO: Low-Rank Hypernetwork for Handling Missing Modalities

LARGO uses low-rank weight-space hypernetworks via CP decomposition to unify missing-modality models, outperforming state-of-the-art on BraTS and ISLES benchmarks.

Niels Vyncke, Pooya Ashtari, Aleksandra Pizurica

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

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 2/5