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Image Generation for Automotive Lidar Open-vocabulary Semantic Segmentation

Nermin Samet, Gilles Puy, Renaud Marlet

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

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2/20 AI panelreviewers recommend it

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
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V-GIFT: Boosting Visual Instruction Tuning with Self-Supervised Guidance

Sophia Sirko-Galouchenko, Monika Wysoczańska, Andrei Bursuc, Nicolas THOME 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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1/20 AI panelreviewers recommend it

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
74%Highly rated
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Test-Time Conditioning with Representation-Aligned Visual Features

REPA-G uses representation-aligned visual features to steer diffusion sampling at inference time via optimized similarity, enabling precise multi-scale and multi-concept conditioning without retraining.

Nicolas Sereyjol-Garros, Ellington Kirby, Victor Letzelter, Victor Besnier and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 0/5
72%Highly rated
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Position: Let’s Strengthen Verifiability if We Can’t Enforce Reproducibility

Machine learning papers are hard to reproduce due to missing code, so researchers should prioritize verifiable results through concrete checkability improvements.

Samet Hicsonmez, Nermin Samet, Renaud Marlet

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 0/5
78%Highly rated
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Progressive Risk Estimation for Accident Anticipation

PRE-ACT models accident risk as a continuously evolving signal that increases approaching crashes, enforcing temporal ordering and distance awareness to suppress false alarms and improve anticipation performance.

Samet Hicsonmez, Eray Çakar, Nermin Samet, Fatma Guney

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
78%Highly rated
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Position: Semantic Uncertainty Measures Disagreement, Not Reliability

Semantic uncertainty measures answer disagreement rather than reliability, as valid answers vary and repeated errors appear certain; a bias-uncertainty decomposition separates variability from systematic error to improve evaluation.

Joseph Hoche, Maxime Corlay, David Brellmann, Andrei Bursuc and 3 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: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5