Showing papers from École Polytechnique Show all papers
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · 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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Standard uniform diffusion training uses a leave-one-out posterior rather than the true denoising posterior, causing a parameterization-objective mismatch that new conversions, samplers, and an absorbing-state reformulation fix to match masked diffusion.
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 4 on Hugging Face · Code ★ 11
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Kernel Token Contradiction uses a token contradiction kernel with von Neumann entropy for fast, accurate LLM claim-level uncertainty quantification. It achieves over 8.2x speedups versus GPU cross-encoders and 65x versus CPU baselines while matching or exceeding accuracy, especially in high-precisio
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Discrete Flow Matching achieves non-asymptotic KL and total variation convergence bounds under minimal approximation error assumptions with improved scaling in vocabulary size and dimension.
Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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D2D converts non-differentiable detectors into differentiable critics via custom activations to guide text-to-image numeracy, substantially improving object counting with minimal quality loss.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 3 on Hugging Face
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Optimal transport characterizes relaxed fair regression via smooth population-wide or exact subset parity penalties across aware and unaware settings, and proposed algorithms match or exceed state-of-the-art benchmarks.
Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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A direct Nadaraya-Watson estimator for Schrödinger bridge time-series drifts achieves uniform non-asymptotic bounds, a pointwise CLT, and adaptive minimax optimality by isolating statistical error from optimization errors.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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FedSARSA with linear approximation and local training achieves linear agent speed-up and converges despite heterogeneous transitions and rewards, with explicit sample and communication complexity bounds.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Focal log-frequency loss balances spectral learning signals in flow matching, accelerating convergence by 40% and improving image fidelity without architectural changes.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Semantic uncertainty measures answer disagreement rather than reliability, as valid answers vary and repeated errors appear certain; a bias-uncertainty decomposition separates variability from systematic error to improve evaluation.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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