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Showing papers from Mila, U. Montreal Show all papers

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NeurIPS 2026Mila / Université de MontréalMila - Quebec Artificial IntelliMcGillU Montreal, MilaMila, U. MontrealDeep RL

Representation Learning Enables Scalable Multitask Deep Reinforcement Learning

Predictive representation learning combined with high-capacity value approximation drives scalable multitask RL, with the simple model-free MR.Q outperforming world-model methods across continuous control tasks.

Johan Obando Ceron, Lu Li, Scott Fujimoto, Pierre-Luc Bacon and 2 more

Sydney Poster Session 4, Wed, Dec 9, 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 4/5
medium 8/10
strict 1/5
71%Highly rated
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NeurIPS 2026U OxfordMila / Université de MontréalGoogle DeepMind / U. de MontrealMila, U. MontrealUSIMechanistic interpretability

A Mechanistic Analysis of Looped Reasoning Language Models

Looped reasoning models converge to cyclic fixed points that stabilize attention and repeat feedforward inference stages iteratively, with recurrence size and normalization affecting stability.

Hugh Blayney, Alvaro Arroyo, Johan Obando Ceron, Pablo Samuel Castro and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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6/20 AI panelreviewers recommend it

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AI panel: 6 of 20 reviewers recommend it
lenient 3/5
medium 3/10
strict 0/5
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NeurIPS 2026Université de MontréalLeidenDelft University of TechnologyMila, U. MontrealPhysics-informed ML & PDEs

One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective

Treating neural quantum state optimization as advantage policy-gradient enables PWO, a trust-region algorithm that improves stability and scales to 1.5B parameters.

Juan A Duque, Sergio García Heredia, Vinicius Hernandes, Eliska Greplova and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 2/5
medium 8/10
strict 2/5
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NeurIPS 2026SpotlightFudanHong Kong University of Science Mila / Université de MontréalCity University of Hong KongHong Kong University of Science Deep RL

Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions

Gaussian trust region reshaping replaces monotonic divergence penalties with bounded non-monotonic constraints, unlocking efficient behavior transitions in non-stationary reinforcement learning.

Bingxu Liu, Jiashun Liu, Johan Obando Ceron, Hao Wang and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 1/5
80%Must read
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NeurIPS 2026MilaGoogle / CornellGoogle ResearchMila, U. MontrealLong-context modeling

Proteus: Incremental Memory Activation for Long-Context Sequence Modeling

Proteus progressively expands memory capacity during long-context modeling to reduce interference and boost retention, consistently improving state-of-the-art memory architectures.

Reza Bayat, Ali Behrouz, Vahab Mirrokni, Aaron Courville

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

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5