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Showing papers from McGill University & Mila - Quebec AI Institute Show all papers

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NeurIPS 2026The Hong Kong PolytechnicMcGill University & Mila - QHong Kong PolytechnicTongji universityTongjiDeep RL

Preference-Guided Adversarial Policy Optimization for Long-Tail Robust Driving

Tong Nie, Yihong Tang, Junlin He, Yuewen Mei and 4 more

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

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medium 0/10
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76%Highly rated
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NeurIPS 2026The Hong Kong PolytechnicTongji universityHong Kong PolytechnicMcGill University & Mila - QTongjiAdversarial robustness

World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning

Adversarial World Modeling casts robust planner learning as a constrained min-max game solved via decoupled self-play, yielding competitive closed-loop performance in nominal and adversarial traffic scenarios.

Tong Nie, Yuewen Mei, Junlin He, Yihong Tang and 2 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · 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 4/5
medium 6/10
strict 0/5