ICLR 2025PastGenerative modelsTheory
ICLR 2025 Workshop on Deep Generative Model in Machine Learning: Theory, Principle and Efficacy
ICLR 2025 DeLTa Workshop
- Submission deadline
- Feb 12, 2025, 00:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (125)
Fetched from OpenReview (v2) on 2026-06-10.
A Reversible Solver for Diffusion SDEs
A Simple Model of Inference Scaling Laws
A Theory for Conditional Generative Modeling on Multiple Data Sources
A Unified Diffusion Bridge Framework via Stochastic Optimal Control
ADAPTIVE HETEROGENEOUS GRAPH REPRESENTATION LEARNING USING KNN-AUGMENTED GRAPH MAMBA NETWORKS (KA-GMN)
An Improved Sample Complexity for Rank-1 Matrix Sensing
AtropDiff: Data-Scarce Atropisomer Generation via Multi-Task Pretrained Classifier-Guided Diffusion
Attention Scheme Inspired Softmax Regression
Balanced Latent Space of Diffusion Models for Counterfactual Generation
Breaking the Likelihood--Quality Trade-off in Diffusion Models by Merging Pretrained Experts
BridgeVoC: Insights into Using Schrödinger Bridge for Neural Vocoders
Building A Unified AI-centric Language System: analysis, framework and future work
Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
Causal Representation Learning and Inference via Mixture-Based Priors
Cellular-Guided Graph Generative Model
Chimera: State Space Models Beyond Sequences
CoDe: Blockwise Control for Denoising Diffusion Models
Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
DDPM Score Matching Is Asymptotically Efficient
DEEP CLUSTERING USING ADVERSARIAL NET BASED CLUSTERING LOSS
Demystifying Long Chain-of-Thought Reasoning in LLMs
Demystifying the Token Dynamics of Deep Selective State Space Models
Design Editing for Offline Model-based Optimization
Designing Parameter and Compute Efficient Diffusion Transformers using Distillation
Diffusion Models Do Not Implicitly Learn Conditional Independence
DIFFUSION MODELS LEARN LOW-DIMENSIONAL DISTRIBUTIONS VIA SUBSPACE CLUSTERING
Diffusion-Based Planning for Autonomous Driving with Flexible Guidance
DIME: Deterministic Information Maximizing Autoencoder
Distance-Based Tree-Sliced Wasserstein Distance
DOSE3 : Diffusion-based Out-of-distribution detection on SE(3) trajectories
Edge-preserving noise for diffusion models
EDM2+: Exploring Efficient Diffusion Model Architectures for Visual Generation
Efficient Consistency Model Training for Policy Distillation in Reinforcement Learning
Efficient Distributed Optimization under Heavy-Tailed Noise
Efficient Knowledge Distillation via Curriculum Extraction
Efficient Molecular Conformer Generation with SO(3) Averaged Flow-Matching and Reflow
Efficient Multi-View Driving Scenes Generation Based on Video Diffusion Transformer
Entropic Time Schedulers for Generative Diffusion Models
Flow Along the K-Amplitude for Generative Modeling
Flow Matching Neural Processes
Flows don't cross in high dimension
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions
Frame Generation in Hilbert Space: Generative Interpolation of Measurement Data for Quantum Parameter Adaptation
FullDiffusion: Diffusion Models Without Time Truncation
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
Gauge Flow Matching for Efficient Constrained Generative Modeling over General Convex Set
Graph Discrete Diffusion: a Spectral Study
GRAPH GENERATIVE PRE-TRAINED TRANSFORMER
Graph transformers express monadic second-order logic
Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold
Gumbel-Softmax Score and Flow Matching for Discrete Biological Sequence Generation
Hidden in the Noise: Two-Stage Robust Watermarking for Images
Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts
High-Order Matching for One-Step Shortcut Diffusion Models
How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
How Well Does Your Tabular Generator Learn the Structure of Tabular Data?
Identifiable Object Representations under Spatial Ambiguities
Identifying metric structures of deep latent variable models
Image Interpolation with Score-based Riemannian Metrics of Diffusion Models
Image-Alchemy : Advancing Subject Fidelity in Personalized Text-to-Image Generation
Implicit Bayesian Inference is An Insufficient Explanation of Language Model Behaviour in Compositional Tasks
Improved Techniques for Training Smaller and Faster Stable Diffusion
Improving Single Noise Level Denoising Samplers with Restricted Gaussian Oracles
Improving Vector-Quantized Image Modeling with Latent Consistency-Matching Diffusion
INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators
Interleaved Gibbs Diffusion for Constrained Generation
LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities
LapLoss: Laplacian Pyramid-based Multiscale Loss for Image Translation
Large Language Diffusion Models
Latent Diffusion U-Net Representations Contain Positional Embeddings and Anomalies
LEARNING STRAIGHT FLOWS BY LEARNING CURVED INTERPOLANTS
Leveraging shared feature representation in cross-domain alignment of decision thresholds for electronic health records data.
Mamba State-Space Models Are Lyapunov-Stable Learners
Masked Generative Nested Transformers with Decode Time Scaling
MCM: Multi-layer Concept Map for Efficient Concept Learning from Masked Images
Measuring Semantic Information Production in Generative Diffusion Models
Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Multi-view Geometry-Aware Diffusion Transformer for Indoor Novel View Synthesis
Neural Genetic Search in Discrete Spaces
Nonparametric Distributional Black-box Optimization via Diffusion Process
On Distilling Generator Matching Models
On the Cone Effect in the Learning Dynamics
On the Power of Context Enhanced Learning in LLMs
On the Query Complexity of Verifier-Assisted Language Generation
Optimizing GPT for Video Understanding: Zero-Shot Performance and Prompt Engineering
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models
PAC Privacy Preserving Diffusion Models
Path Planning for Masked Diffusion Models with Applications to Biological Sequence Generation
Phase-aware Training Schedule Simplifies Learning in Flow-Based Generative Models
PHYSICS-INFORMED GENERATIVE APPROACHES FOR WIRELESS CHANNEL MODELING
Probability-Flow ODE in Infinite-Dimensional Function Spaces
Provable Maximum Entropy Manifold Exploration via Diffusion Models
Remasking Discrete Diffusion Models with Inference-Time Scaling
Revisiting Noise Schedule Design for Diffusion Training
Reward-Guided Diffusion Model for Data-Driven Black-Box Design Optimization
RFMI: Estimating Mutual Information on Rectified Flow for Text-to-Image Alignment
Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control
Solving Bayesian inverse problems with diffusion priors and off-policy RL
SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting
Spherical Tree-Sliced Wasserstein Distance
Stable Consistency Tuning: Understanding and Improving Consistency Models
Statistical Foundations of Conditional Diffusion Transformers
StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces
Symmetry Is All You Need: Image Generation Using Pre-trained Deep Diffusion Probabilistic Models
Symmetry-Preserving Diffusion Models via Target Symmetrization
TASKD-LLM: Task-Aware Selective Knowledge Distillation for LLMs
The Diffusion Duality
The Space Between: On Folding, Symmetries and Sampling
Towards Black-Box Membership Inference Attack for Diffusion Models
Towards Training One-Step Diffusion Models Without Distillation
Towards Variational Flow Matching on General Geometries
TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models
Training Consistency Models with Variational Noise Coupling
Trustworthy Image Super-Resolution via Generative Pseudoinverse
Unifying Autoregressive And Diffusion-Based Sequence Generation
Unifying Causal and Object-centric Representation Learning allows Causal Composition
UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation
Unpaired Point Cloud Completion using Unbalanced Optimal Transport Map
Variational Rectified Flow Matching
Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation
Weak-to-Strong Diffusion with Reflection
Your Image is Secretly the Last Frame of a Pseudo Video