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Generative Models

197 papers

Papers per year

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Papers

Generating Synthetic Relational Tabular Data via Structural Causal Models ACL 2025
PatchDPO: Patch-level DPO for Finetuning-free Personalized Image Generation CVPR 2025
Mitigating Hallucinations in LM-Based TTS Models via Distribution Alignment Using GFlowNets EMNLP 2025
EnAnchored-X2X: English-Anchored Optimization for Many-to-Many Translation EMNLP 2025
End-to-End Aspect-Guided Review Summarization at Scale EMNLP 2025
Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing ICCV 2025
MamTiff-CAD: Multi-Scale Latent Diffusion with Mamba+ for Complex Parametric Sequence ICCV 2025
TFG: Unified Training-Free Guidance for Diffusion Models NIPS 2024
On conditional diffusion models for PDE simulations NIPS 2024
Generative Fractional Diffusion Models NIPS 2024
Geometric Trajectory Diffusion Models NIPS 2024
Fast samplers for Inverse Problems in Iterative Refinement models NIPS 2024
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization NIPS 2024
Towards Editing Time Series NIPS 2024
Debiasing Synthetic Data Generated by Deep Generative Models NIPS 2024
Genetic-guided GFlowNets for Sample Efficient Molecular Optimization NIPS 2024
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization NIPS 2024
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions NIPS 2024
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems NIPS 2024
Equivariant Neural Diffusion for Molecule Generation NIPS 2024
Frequency-aware Generative Models for Multivariate Time Series Imputation NIPS 2024
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms NIPS 2024
Cascade of phase transitions in the training of energy-based models NIPS 2024
Improving the Training of Rectified Flows NIPS 2024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling NIPS 2024