Showing papers from Mila Show all papers
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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LLM-based cellular perturbation reasoning relies on intrinsic gene tendencies rather than true perturbation effects, and contrastive evidence organization improves prediction accuracy substantially.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Learned stochastic stopping reduces out-of-distribution variance in looped transformers by decoupling loop count from sequence length during training. It improves accuracy-stability trade-offs across algorithmic tasks, though it can stabilize suboptimal computation.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Self-supervised pre-training on one real table yields strong tabular transfer, where feature count predicts usefulness and in-context generalization is retrieval-based.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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A framework samples coherent but cognitively unavailable "alien" research directions by maximizing idea coherence while minimizing existing community availability, broadening explored vocabularies 3.5-7x over LLM baselines.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Fixed weighted penalties poorly enforce hard deep learning constraints; use constrained formulations directly instead of scalarized surrogates.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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CCBR builds recommendations from textual user profiles via content-derived text bottlenecks, enabling controllable multimodal steering with competitive accuracy across image, audio, and video datasets.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Reasoning is formalized via optimal transport to bound transformers' OOD generalization by architectural Lipschitz continuity and approximation limits, proving depth is needed for backtracking and shift-invariant attention reduces risk.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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GeneZip uses region-aware compression to achieve high base-pairs-per-token ratios, improves DNA modeling benchmarks, and enables 128K-context training on limited hardware.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Proteus progressively expands memory capacity during long-context modeling to reduce interference and boost retention, consistently improving state-of-the-art memory architectures.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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