Conditional Diffusion Models

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20 papers in the last four weeks, up 233% on the four weeks before. 0.2% of all new papers.

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PCGD: Physics-Guided Conditional Graph Diffusion for TCAD Device Simulation
Jun 28, 2026Yihan Zhang, Zhiteng Zhang, Kun Chen +1PDE Surrogate Modeling Physics-Informed ML
LISA: Likelihood Score Alignment for Visual-condition Controllable Generation
Jun 25, 2026Yanghao Wang, Hongxu Chen, Jiazhen Liu +4Score-Based Generative Modeling Controllable Video Generation
The Hong Kong University of Science and Technology · Huawei Research
Proposal-Conditioned Latent Diffusion for Closed-Loop Traffic Scenario Generation
Jun 25, 2026Shubham Vaijanath Phoolari, Aleyna Kara, Christoph Lauer +1Diffusion Guidance Diffusion Model Acceleration
Authors are with CARIAD SE, Germany. · Author is with the Institute of Automotive Engineering (FZD), TU Darmstadt, Germany. · Author is with the Technical University of Munich, Germany.
Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics
Jun 24, 2026Miguel Angel Rogel Garcia, Phone Thiha Kyaw, Jonathan KellyNeural Representation Geometry Conditional Diffusion Models
Institute for Aerospace Studies, University of Toronto, Toronto, Canada
Sampling sea state using a diffusion model
Jun 24, 2026Jiarong Wu, Bertrand Chapron, Laure ZannaTime Series Forecasting Probabilistic Forecasting
Courant Institute School of Mathematics, Computing and Data Science, New York University, 251 Mercer Street, New York, 10012, NY, USA. · Laboratoire d’Oc´eanographie Physique et Spatiale (LOPS), Ifremer, 1625 route de Sainte-Anne, Plouzan´e, 29280, Bretagne, France.
TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs
Jun 24, 2026Junhyeok Lee, Kyu Sung ChoiLatent Diffusion Models Accelerated MRI Reconstruction
Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine · Department of Radiology, Seoul National University Hospital · Department of Radiology, Seoul National University College of Medicine +1
Spatio-Temporal Mixture-of-Modality-Experts Diffusion for Quantitative DCE-MRI Synthesis from Incomplete MR Sequences
Jun 24, 2026Junhyeok Lee, Kyu Sung ChoiMedical Image Synthesis Mixture-of-Experts Models
Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine · Department of Radiology, Seoul National University Hospital · Department of Radiology, Seoul National University College of Medicine +1
Anatomically-conditioned Latent Diffusion Model for Data-Efficient Few-Shot Cross-Domain 3D Glioma MRI Synthesis
Jun 24, 2026Salman Shaik, Truong Thanh Hung Nguyen, Hung CaoLatent Diffusion Models Medical Image Synthesis
Analytics Everywhere Lab, University of New Brunswick, Canada
Catastrophic Compositional Generation: Why Vanilla Diffusion Models Fail to Extrapolate
Jun 22, 2026Duncan Soiffer, Chandler Squires, Yuan Guan +2OOD Generalization Conditional Diffusion Models
Machine Learning Department, Carnegie Mellon University · Valence Labs · Department of Computer Science, University of Manchester
ARIA: Adaptive Region-Based Importance Allocation for Conditional Diffusion Distillation
Jun 22, 2026Loay Mualem, Vinh Tong, Samir Darouich +1Diffusion Model Distillation Teacher-Student Learning
Institute for AI, University of Stuttgart · IMPRS-IS · Institute of Theoretical Chemistry, University of Stuttgart.
C^2GR: Coupled Comprehensive Generative Replay for a Continually Learnable Universal Segmentation Model
Jun 22, 2026Wei Li, Jingyang Zhang, Guoan Wang +4Cross-Modality Medical Image Segmentation Replay-Based Continual Learning
Shanghai Jiao Tong University · Southeast University · Stevens Institute of Technology +2
Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting
Jun 22, 2026Falguni Ghosh, Vahid Hashemi, Bernhard KainzLong-Term Time Series Forecasting Probabilistic Forecasting
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, 91052, Germany · AUDI AG, Auto-Union-Straße 1, 85057 Ingolstadt, Germany · Imperial College London, London SW7 2RH, United Kingdom
Bridging Self-Supervised Learning and Speech Enhancement: A Wav2Vec2-Conditioned Framework
Jun 21, 2026Shuubham Ojha, Carol Espy-WilsonAudio Diffusion Models Speech Enhancement
Institute for Systems Research, University of Maryland, College Park
2D Versus 3D Diffusion for In Silico Training of Interventional X-ray AI Models
Jun 19, 2026Sampath Rapuri, Jeremy Ko, Benjamin D. Killeen +2Synthetic Data Augmentation Medical Imaging
Johns Hopkins University, Baltimore, MD 21218, USA
Atomistic Language Models Understand and Generate Materials
Jun 19, 2026Sathya Edamadaka, Krithik Ramesh, Ju Li +1Crystal Structure Prediction Language Modeling
Massachusetts Institute of Technology · Lyra Labs · Lila Sciences
UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion
Jun 18, 2026Aryan Das, Koushik Biswas, Moloud Abdar +1Compositional Image Generation Conditional Diffusion Models
VIT Bhopal, India · IIIT Delhi, India · The University of Queensland, Australia +1
Repurposing a Speech Classifier for Guided Diffusion-Based Speech Generation
Jun 18, 2026Rostislav Makarov, Timo GerkmannDiffusion Model Guidance Audio Diffusion Models
University of Hamburg, Germany
FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows
Jun 18, 2026Daniel Gilo, Sven Elflein, Ido Sobol +1Diffusion Model Alignment Diffusion Models for Image Restoration
1Technion · 2NVIDIA · University of Toronto +1
MakeupMirror: Improving Facial Attribute Preservation in Diffusion Models for Makeup Transfer
Jun 18, 2026Nefeli Andreou, Angel Martínez-González, Sabine Sternig +3Image Style Transfer Diffusion-Based Image Editing
Amazon
One-Shot Novel View and Pose Human Image Synthesis via 3D Prior Guided Diffusion Model
Jun 18, 2026Shenjian Gong, Kangkan Wang, Shanshan Zhang +1Image Generation Novel View Synthesis
PCA Lab, Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, and Jiangsu Key Lab of Image and Video Understanding for Social Security, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094 China
Approximate Structured Diffusion for Sequence Labelling
Jun 17, 2026Nicolas Floquet, Joseph Le Roux, Nadi TomehConditional Random Fields Morphosyntactic Tagging
Université Sorbonne Paris Nord, CNRS, Laboratoire d’Informatique de Paris Nord, LIPN, F-93430 Villetaneuse, France
Structural MRI Synthesis for Alzheimer's Disease via Conditional Diffusion on Anatomical Masks
Jun 16, 2026Muge Zhang, Muhammad Ali Khaliq, Jamal Alsakran +2Synthetic Data Augmentation Alzheimer's Disease
Fairleigh Dickinson University, Vancouver, BC, Canada · University of Colorado at Colorado Springs, Colorado Springs, CO, USA
Constrained Diffusion Models with Primal-Dual Inference
Jun 15, 2026Samar Hadou, Yigit Berkay Uslu, Alejandro RibeiroPrimal-Dual Optimization Constrained Generative Modeling
Department of Electrical and Systems Engineering University of Pennsylvania
RAID: Semantic Graph Diffusion for True Cold-Start and Cross-Lingual Forecasting
Jun 15, 2026Arunkumar V, Manoranjan Gandhudi, Gangadharan G. R. +2Time Series Forecasting Retrieval-Augmented Time Series Forecasting
University College of Engineering, Anna University Tiruchirappalli, Tamil Nadu, India · Central University of Karnataka, India · National Institute of Technology Tiruchirappalli, India +1
Unified Audio Generation and Editing via Joint Condition Modeling and Progressive Training
Jun 15, 2026Haocheng Dong, Yuheng Lu, Cheng Gong +3Text-to-Audio Generation Audio Editing
Department of Electronic Engineering and Information Science, University of Science and Technology of China, China · Institute of Artificial Intelligence of China Telecom (TeleAI), China · Tianjin Key Laboratory of Cognitive Computing and Application, School of Artificial Intelligence, Tianjin University, China
Lesion-DDPM: Lesion-Enhanced 3D Diffusion for MS MRI Synthesis
Jun 13, 2026Weidong Zhang, Yongchan Jung, Shafayat Mowla Anik +5Medical Image Synthesis Diffusion MRI
Northeastern University, Vancouver, BC · Fairleigh Dickinson University, Vancouver, BC · University of Colorado at Colorado Springs, Colorado Springs, CO +2
HemExp: Clinically-Guided Latent Diffusion for Modeling Hematoma Expansion
Jun 13, 2026Orhun Utku Aydin, Satoru Tanioka, Tzu I Chuang +7Longitudinal Medical Image Analysis Clinical Prediction
CLAIM – Charité Lab for AI in Medicine, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany · Department of Neurosurgery, Mie Chuo Medical Center, 2158-5 Myojin-cho,2026 514-1101, Hisai,Tsu, Japan
Task-Aware Environment Augmentation for Reliable Navigation via Shielded Conditional Diffusion
Jun 13, 2026Bharawee Phoompho, Gokul Puthumanaillam, Yan Miao +4Robot Navigation Conditional Diffusion Models
University of Illinois Urbana-Champaign
Multiscale Hypersonic Boundary Layer Reconstruction via Spectral Binning and Subdomain-wise Conditional Diffusion
Jun 12, 2026Hojin Kim, Dibyajyoti Chakraborty, Takahiko Toki +2Neural Surrogate Modeling Conditional Diffusion Models
School of Mechanical Engineering, Purdue University, West Lafayette, 47907, IN, USA · College of Information Sciences and Technology, Pennsylvania State University, University Park, 16802, PA, USA · Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, 60439, IL, USA
Regional Climate Model Emulation with Diffusion Approaches: What is the Added Value of Generative Machine Learning?
Jun 12, 2026Mikel N. Legasa, Antoine Doury, Achille Gellens +4Surrogate Modeling Precipitation Downscaling
Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA/CNRS/UVSQ, Universit´e Paris Saclay, UMR8212, 91191 Gif-sur-Yvette, France · CNRM, Universit´e de Toulouse, M´et´eo-France, CNRS, Toulouse, France · Institut Pierre-Simon Laplace (IPSL), FR636, Paris, France +1

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PCGD: Physics-Guided Conditional Graph Diffusion for TCAD Device Simulation

Yihan Zhang, Zhiteng Zhang, Kun Chen, Chen Wang

PDE Surrogate Modeling Physics-Informed ML Conditional Diffusion Models Physics-Based Simulation Graph Diffusion

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Technology computer-aided design (TCAD) semiconductor device simulation is fundamentally constrained by the high computational cost of iteratively solving coupled drift-diffusion equations. Existing ML surrogates either reduce internal physics to macroscopic scalar regressions, or rely on single-step mappings that lack the iterative refinement required to resolve stiff, coupled fields. To address this, we introduce PCGD, a Physics-Guided Conditional Graph Diffusion framework operating natively on unstructured TCAD meshes to predict coupled electrostatic and carrier density fields. PCGD employs a Condition-Aware MeshGraphNet denoiser that explicitly injects boundary conditions and device structure context via global cross-attention. By augmenting data-driven denoising with a physics-guided hybrid objective that integrates exponent-free quasi-Fermi gradient matching with noise-aware PDE residuals, PCGD progressively enforce physical constraints in the iterative diffusion trajectory. This strategy successfully bypasses the numerical instabilities typical of stiff drift-diffusion equations. Evaluated on a challenging mixed PN/MOS benchmark, PCGD significantly outperforms deterministic one-step regression (1.207% error) and local diffusion (1.585% error) baselines by achieving a sub-percent mean relative field error of 0.835%, while concurrently reducing maximum PDE residual errors by nearly three orders of magnitude compared to pure diffusion. It also transfers robustly to unseen SOI topologies (0.815% error) via LoRA adaptation, using 5.30

\times

less data and 14.34

\times

fewer parameters than full fine-tuning. Ultimately, PCGD bridges the computational efficiency of generative surrogates with the rigorous physical fidelity of traditional TCAD, unlocking highly scalable, field-level analysis for robust device engineering.

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