Showing Flow matching Show all papers
Sydney Poster Session 6, Thu, Dec 10, 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 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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Sydney Poster Session 6, Thu, Dec 10, 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 5, Thu, Dec 10, 10:00 AM–1:00 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 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · 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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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · 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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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · 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 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · 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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SelFix selects fixed-point solutions by trajectory straightness for rectified flow inversion, improving reconstruction and editing accuracy.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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LucidNFT improves flow-based real-world super-resolution via LR-anchored multi-reward preference optimization that reduces hallucinations while preserving perceptual quality.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Truncated signature inversion is reframed as learning conditional path distributions via signature-conditioned flow matching, with derived Bayes error baselines and validated reconstruction on real data.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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TACache decomposes rectified flow velocity errors into magnitude and direction components to skip steps and reconstruct velocities without extra evaluations, achieving up to 4.14x faster image and 2.11x faster video generation.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Ill-conditioned intermediate covariances make flow matching regress low-variance directions slowly; preconditioning into isotropic space improves optimization and generation quality.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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VTV-FM enables second-order flow matching via a minimum-acceleration variational terminal-velocity closure for static data, improving transport geometry and generation quality.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Condition-dependent source distributions for flow matching improve text-to-image generation via variance regularization and directional alignment, accelerating convergence up to 3x in FID.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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kFFM replaces arbitrary pairing in Functional Flow Matching with kernel optimal transport to improve infinite-dimensional generative modeling and outperforms baselines on time-series and PDE benchmarks.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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RWEFM generatively models meta-distributions on manifolds via Riemannian Wasserstein flow matching, yielding valid flows and efficient GPU-optimal transport approximations for non-Euclidean data.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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GenRec separates reconstruction and generation via observation masks to preserve fidelity in visible regions while synthesizing plausible unobserved content.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Flow map denoisers implicitly define a one-parameter family spanning the distortion-perception tradeoff via lookahead parameter t, matching or exceeding specialized baselines across inverse problems.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · 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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World Motion Models unify dynamic 3D entities via sparse SE(3) trajectories and flow-matching, enabling any-to-any conditioning across prediction, control, and retargeting tasks.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Flow matching with over-parameterized 2-layer ReLU networks achieves convergence, generalization, and sample-generation Wasserstein guarantees via multi-task representation bounds.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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CFM and forward-only IFM are equivalent via a bijection, but general IFM is strictly more expressive, yielding cross-framework techniques.
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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STREAM applies Riemannian flow matching to histopathology VFM patch-token features on the hypersphere to avoid conditioning collapse, achieving state-of-the-art synthetic image generation via a stochastic bridge and anisotropic decoder.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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SCFM augments flow matching with structured latent variables and a shared recognition network to jointly learn structured priors and continuous transport maps, enabling unsupervised clustering and disentanglement without sacrificing generative quality.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · Code ★ 1
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Active Flow Expansion uses verifier-guided active exploration to grow a flow model's generable set, yielding theoretical guarantees and superior out-of-distribution molecule and protein design.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Classifier-based adaptive stopping treats MCMC trajectory termination as learnable via GFlowNets, reducing trajectory lengths while improving mode coverage and mixing.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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PGFM introduces flow matching for generative dataset distillation with deterministic ODE synthesis, continuous path-to-prototype guidance, and 7.6x efficiency gains over diffusion methods.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Nonasymptotic total variation analysis of Riemannian flow matching bounds sampling error by discretization and learning terms via curvature-aware differential inequalities. Explicit polynomial iteration complexities follow on hyperspheres and SPD manifolds.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Flow Perturbation++ performs multi-step unbiased Jacobian estimation for continuous normalizing flows, reducing variance to improve high-dimensional Boltzmann sampling.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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gfnx is a JAX library for training and evaluating GFlowNets that achieves up to 80x speedups over PyTorch benchmarks across diverse tasks.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Residual Latent Action predicts visual feature dynamics via flow matching, outperforming diffusion world models with orders-of-magnitude faster inference and enabling offline robot learning from videos.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 47
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A discrete-time stochastic control formulation yields value-driven transport policies that generate data via straight, fast, robust paths and support conditional generation and guidance.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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TracingFlow is a simulation-free flow matching framework using second-order dynamics and acceleration fields to infer continuous system evolution from sparse snapshots, achieving superior trajectory and distribution accuracy.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Optimal transport conditional flow matching equals exact proximal operators via extended Brenier potentials without density assumptions, yields explicit vector fields, converges with batch size, and contracts exponentially normal to manifold-supported targets.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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CCVFM replaces isotropic noise with a coreset-derived Gaussian mixture source for hierarchical rectified flow, using a lightweight correction flow for residuals to achieve competitive few-step generation.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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DeCAF distills all-atom biomolecular cofolding diffusion models into few-step flow maps with SE(3)-aligned endpoint losses, improving accuracy and physical validity at strict inference budgets.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A flow matching framework learns disentangled representations via factor-conditioned flows and orthogonality regularization, improving disentanglement, controllability, and sample fidelity over diffusion baselines.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Drift Flow Matching bridges one-step drift models and iterative flow matching to enable adaptive sampling computation for flexible generation quality and efficiency.
Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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HTFM models heavy-tailed sources as mixtures of clock-conditioned Gaussians to improve mode coverage, sample quality, and tail recovery over Gaussian flow matching while enabling tail calibration via clock laws.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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GeoCore-9B is a 9-billion-parameter diffusion model trained from scratch on global earth observation data that conditions generation on geospatial metadata and achieves state-of-the-art visual fidelity and geographic accuracy.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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FSF-DMD eliminates the fake-score network in DMD for flow-map generators by using the generator's pseudo-velocity to provide reverse-divergence signals, improving ImageNet FID.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · 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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Straight-line generative flows exist for arbitrary Gaussian endpoints but are impossible for targets with well-separated modes.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Midpoint Generative Models define a midpoint divergence from flow matching symmetry to train one-step generators with competitive results.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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CSFlow aligns flow matching with human contrast sensitivity via timestep weights that match generated spatial frequencies to visual perception, improving image quality and reducing FID by 4.7%.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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AsymFlow restricts noise prediction to a low-rank subspace to recover full-dimensional velocity, achieving 1.57 FID on ImageNet and enabling latent-to-pixel flow finetuning.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 22 on Hugging Face · Code ★ 473
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Manifold drift pushes flow preference optimization off the data manifold via terminal displacement normal components; ThermoDPO-weighted improves strict score and image metrics over FlowDPO.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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SCALLOP introduces a Hutchinson-free likelihood distillation objective for few-step Boltzmann generators, reducing training variance and time while achieving up to 10x inference speedup.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Flow models relate to Schrödinger dynamics via an unusual Hamiltonian, enabling efficient quantum Hamiltonian simulation for preparing coherent encodings of flow-modeled distributions and supporting quantum statistical algorithms.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Reflow distillation under-determines endpoint distribution by trajectory matching; adding a marginal-alignment regularizer improves few-step generation quality with theoretical guarantees.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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FLOWGEM uses approximate Wasserstein gradient flows to generate complete data from non-monotone MAR patterns by minimizing observed-data KL divergence, achieving state-of-the-art results.
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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