Good Papers

Showing papers from Mila / École Polytechnique de Montréal Show all papers

57%Worth a look
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Addressing Sparse-Rewards in RL with Scalable Hierarchical Novel Eigen Options

Priyesh Vijayan, Élodie Côté-Gauthier, Mathieu Reymond, Sarath Chandar and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · 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
67%Highly rated
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Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models

Nilaksh, Saurav Jha, Artem Zholus, Sarath Chandar

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · 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
83%Must read
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Dialectics of Alignment: Harnessing Unsafe Knowledge for Dynamic Safety Routing

SafeMoE isolates unsafe knowledge into domain-specific LoRA experts and routes them with a lightweight gating network to improve safe response rates by over 20% relative while maintaining informative outputs.

Maryam Hashemzadeh Barvarz, Jerry Huang, Minseon Kim, Marc-Alexandre Côté and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 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
78%Highly rated
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Sparse Koopman Autoencoders Identify Local Dynamical Regimes in Multibasin Systems

Sparse Koopman autoencoders use sparse latent supports as label-free regime indicators that identify local dynamical basins and outperform dense autoencoders in multibasin forecasting.

Aidan Li, Uday Kiran Reddy Tadipatri, Mahan Fathi, Sarath Chandar and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · 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 3/5
medium 8/10
strict 0/5