Compositional Diffusion with Guided search for Long-Horizon Planning
Introduces CDGS integrating compositional diffusion with guided search for coherent long-horizon plan generation.
Avg rating: 6.50 (6–8) · Utkarsh Aashu Mishra et al.
Diffusion & Flow Matching
Diffusion models, score-based generative models, flow matching, consistency models, and related generative techniques.
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Cross-Domain Lossy Compression via Rate- and Classification-Constrained Optimal Transport
Cross-domain lossy compression unifies rate and classification constraints via optimal transport framework.
Avg rating: 6.00 (2–10) · Nam Nguyen et al.
DCFold: Efficient Protein Structure Generation with Single Forward Pass
Distills AlphaFold3 into single-step sampler with temporal geodesic matching achieving 15x inference acceleration.
Avg rating: 5.50 (4–8) · Zhe Zhang et al.
FALCON: Few-step Accurate Likelihoods for Continuous Flows
Triple-BERT addresses order dispatching via centralized SARL with action decomposition and BERT-based attention.
Avg rating: 7.00 (4–10) · Danyal Rehman et al.
Generating metamers of human scene understanding
EditVerse unifies image and video generation/editing via token sequences enabling cross-modal knowledge transfer.
Avg rating: 6.67 (6–8) · Ritik Raina et al.
Generative Human Geometry Distribution
Introduces distribution-over-distribution model combining geometry distributions with two-stage flow matching for human 3D generation.
Avg rating: 5.50 (2–8) · Xiangjun Tang et al.
GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models
GLASS Flows samples Markov transitions via inner flow matching models to improve inference-time reward alignment in flow and diffusion models.
Avg rating: 7.00 (6–8) · Peter Holderrieth et al.
Neon: Negative Extrapolation From Self-Training Improves Image Generation
Neon inverts model degradation from self-training by extrapolating away from it, improving generative models with minimal compute.
Avg rating: 7.00 (6–8) · Sina Alemohammad et al.
NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale
NextStep-1 achieves state-of-the-art autoregressive text-to-image generation by modeling continuous image tokens with lightweight flow matching instead of diffusion.
Avg rating: 4.50 (2–6) · Chunrui Han et al.
Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
Pareto-Conditioned Diffusion formulates offline multi-objective optimization as conditional sampling problem avoiding explicit surrogate models.
Avg rating: 6.50 (6–8) · Jatan Shrestha et al.
Planner Aware Path Learning in Diffusion Language Models Training
Theoretical characterization shows MDMs are expressively equivalent to padded looped transformers, more efficient for parallel problems.
Avg rating: 5.50 (4–8) · Fred Zhangzhi Peng et al.
Quotient-Space Diffusion Models
Quotient-space diffusion models reduce learning difficulty for molecular structure generation via SE(3) symmetry handling.
Avg rating: 7.50 (6–10) · Yixian Xu et al.
SAFETY-GUIDED FLOW (SGF): A UNIFIED FRAMEWORK FOR NEGATIVE GUIDANCE IN SAFE GENERATION
SGF unifies negative guidance in safe generation via MMD potentials and control barrier analysis with time-critical guidance windows.
Avg rating: 6.50 (4–10) · Mingyu Kim et al.
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
Proteina-Complexa unifies generative modeling and hallucination for atomistic binder design via pretraining on Teddymer and test-time optimization.
Avg rating: 7.00 (4–10) · Kieran Didi et al.
Stable Video Infinity: Infinite-Length Video Generation with Error Recycling
Generates ultra-long videos by actively correcting self-generated errors through error-recycling fine-tuning.
Avg rating: 6.50 (4–8) · Wuyang Li et al.
The Spacetime of Diffusion Models: An Information Geometry Perspective
Spacetime perspective views diffusion latent spaces as Fisher-Rao metric manifolds enabling efficient geodesic computation without simulation.
Avg rating: 6.50 (4–8) · Rafal Karczewski et al.
TRACE: Your Diffusion Model is Secretly an Instance Edge Detector
TRACE reveals diffusion models encode hidden instance boundary priors and leverages them for unsupervised instance segmentation without dense annotations.
Avg rating: 6.00 (4–8) · Sanghyun Jo et al.
Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)
RealUID provides universal distillation for matching models without GANs, incorporating real data into one-step generator training.
Avg rating: 6.00 (4–8) · Nikita Maksimovich Kornilov et al.