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DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning

DriveDreamer-Policy unifies depth generation, video prediction, and motion planning via geometry-aware world representations, achieving 89.2 PDMS on Navsim v1 and 88.7 EPDMS on v2.

Yang Zhou, Xiaofeng Wang, Hao Shao, Letian Wang and 7 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face · Code ★ 60

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5
76%Highly rated
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LinearARD: Linear-Memory Attention Distillation for RoPE Restoration

LinearARD restores RoPE-scaled LLMs via linear-memory attention self-distillation, recovering 98.3% short-text performance with 4.25M tokens versus 256M.

Ning Yang, Hengyu Zhong, Wentao Wang, Baoliang Tian 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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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 0/5