ICLR 2026 Past Safety & alignmentDiffusion models

Real‑World Constrained and Preference‑Aligned Flow‑ and Diffusion‑Based Models | ICLR 2026 Workshop

ReALM-GEN 2026 - ICLR 2026 Workshop

Submission deadline
Feb 12, 2026, 23:59 AoE (UTC−12)
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Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).

Accepted papers (84)

Fetched from OpenReview (v2) on 2026-06-10.

  1. A Unified Density Operator View of Flow Control and Merging

    Riccardo De Santi, Malte Franke, Ya-Ping Hsieh, Andreas Krause · PDF
  2. A2D2: Finetuning Any-Length Discrete Diffusion for Adaptive Decoding

    Sophia Tang, Yuchen Zhu, Molei Tao, Pranam Chatterjee · PDF
  3. Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective

    Yinan Huang, Hans Hao-Hsun Hsu, Junran Wang, Bo Dai, Pan Li · PDF
  4. Accelerating Diffusion Language Models via Inverse Distillation

    David Li, Nikita Gushchin, Dmitry Abulkhanov, Eric Moulines, Ivan Oseledets, Maxim Panov, Alexander Korotin · PDF
  5. Action-Informed Belief via Latent Flow Matching for Memory-Intensive Robotic Tasks

    Dawei Wang, Xingrui Yu, Zhenglin Wan, Ivor Tsang · PDF
  6. Activation Steering for Masked Diffusion Language Models

    Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit LeVi, Raz Lapid · PDF
  7. Adapting Diffusion Policies to Novel Environments via Policy-Steered Optimization

    Skye Thompson, Sergio Orozco, Eric Rosen, Karl Schmeckpeper, George Konidaris · PDF
  8. Adaptive Order Policies for Masked Diffusion

    Mohsin Hasan, Jama Hussein Mohamud, Mirco Ravanelli, Yoshua Bengio · PDF
  9. Aligning Diffusion Language Models via Unpaired Preference Optimization

    Vaibhav Jindal, Hejian Sang, Chun-Mao Lai, Yanning Chen, Zhipeng Wang · PDF
  10. AReUReDi: Annealed Rectified Updates for Refining Discrete Flows with Multi-Objective Guidance

    Tong Chen, Yinuo Zhang, Sophia Vincoff, Pranam Chatterjee · PDF
  11. Bad-OOD: Discovering Harmful Synthetic Diffusion Outliers via Confidence Calibration

    Donglin Ni, Zhixin Feng, Ke Li, Yue Zhang, Yonggang Qi · PDF
  12. BlockGen: Flexible Blockwise Sequence Modeling with Hybrid Samplers

    Justin Deschenaux, Caglar Gulcehre · PDF
  13. Categorical Reparameterization with Denoising Diffusion models

    Samson Gourevitch, Eric Moulines, Alain Oliviero Durmus, Jimmy Olsson, Yazid Janati · PDF
  14. CausalSliders: Graph-Guided LoRA Interventions for Causally Consistent Image Editing

    Aditi Tiwari, Akshit Bhalla, Darshan Ganesh Prasad, Heng Ji · PDF
  15. CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control

    Riccardo Barbano, Alexander Denker, Runchang Li, Zeljko Kereta, Francisco Vargas · PDF
  16. Constraint-Aware Flow Matching via Randomized Exploration

    Zhengyan Huan, Jacob Boerma, Liping Liu, Shuchin Aeron · PDF
  17. Corruption-Aware Training of Latent Video Diffusion Models for Robust Text-to-Video Generation

    Chika Maduabuchi, Hao Chen, Yujin Han, Jindong Wang · PDF
  18. CupOFMoCA: Coupled Objective-Guided Discrete Flows for Molecular Conjugate Assembly

    Ruoxi Zhang, Jiatao Gu, Pranam Chatterjee · PDF
  19. DDNO: Discrete Diffusion Noise Optimization

    Luca Eyring, Vincent Pauline, Stefan Bauer, Alexey Dosovitskiy, Zeynep Akata · PDF
  20. Decoupling Tilting from Transport: Stable Online Alignment of Flow and Diffusion Policies

    Chubin Zhang, Zhenglin Wan, Feng Chen, Fuchao Yang, Lang Feng, Yaxin Zhou, Xingrui Yu, Yang You, Ivor Tsang, Bo An · PDF
  21. Di3PO - Diptych Diffusion DPO for Targeted Improvements in Image

    Sanjana Reddy, Ishaan Malhi, Sally Ma, Praneet Dutta · PDF
  22. Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps

    Peter Holderrieth, Douglas Chen, Luca Eyring, Ishin Shah, Giri Anantharaman, Yutong He, Zeynep Akata, Tommi Jaakkola, Nicholas Matthew Boffi, Max Simchowitz · PDF
  23. DiffAntiSeq: Target-Steered Diffusion in Latent Sequence Space for Antibody Library Design

    Fang Wu · PDF
  24. Diffuse and Steer: Corrective Sampling for Stable 3D Molecular Diffusion

    Fang Wan, Wenhan Gao, Jingxiang Qu, Yi Liu · PDF
  25. Diffusion Alignment Beyond KL: Variance Minimisation as Effective Policy Optimiser

    Zijing Ou, Jacob Si, Junyi Zhu, Ondrej Bohdal, Mete Ozay, Taha Ceritli, Yingzhen Li · PDF
  26. Diffusion Policy Optimization without Drifting Apart

    Haozhe Jiang, Haiwen Feng, Jiantao Jiao, Angjoo Kanazawa, Nika Haghtalab · PDF
  27. Diffusion Priors for Lightweight Personal- ized Image Generation

    Gabriel A. Patron, Zhiwei Xu, Ishan Kapnadak, Felipe Maia Polo · PDF
  28. Diffusion-Driven Latent Guided Sampling for Neural Combinatorial Optimization

    Sobihan Surendran, Adeline Fermanian, Sylvain Le Corff · PDF
  29. Discrete Diffusion Inference-Time Control With Nested Sequential Monte Carlo

    Lohithsai Yadala Chanchu, Hany Abdulsamad, Christian A. Naesseth · PDF
  30. Disentangled Compositional Diffusion for Controllable Scientific Data Generation

    Nandan Madhuj, Meet Hemant Parikh, Anirban Samaddar, Yixuan Sun, Sandeep Madireddy, Jian-Xun Wang · PDF
  31. Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models

    Abhi Gupta, Polina Barabanshchikova, Vikas K Garg, Samuel Kaski, Tommi Jaakkola · PDF
  32. Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning

    Zifan Wang, Riccardo De Santi, Xiaoyu Mo, Michael M. Zavlanos, Andreas Krause, Karl Henrik Johansson · PDF
  33. Energy-Guided Diffusion for Valid SMILES Generation

    Ivan Gurev, Nikolay Nikitin · PDF
  34. Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization

    Yuchen Zhu, Wei Guo, Jaemoo Choi, Petr Molodyk, Bo Yuan, Molei Tao, Yongxin Chen · PDF
  35. EntRGi: Entropy Aware Reward Guidance for Diffusion Language Models

    Atula Tejaswi, Litu Rout, Constantine Caramanis, Sanjay Shakkottai, sujay sanghavi · PDF
  36. Flexible Locomotion Learning with Diffusion Model Predictive Control

    Runhan Huang, Haldun Balim, Heng Yang, Yilun Du · PDF
  37. Flow-Factory: A unified framework for easy reinforcement learning in Flow-Matching models

    Bowen Ping, Chengyou Jia, Minnan Luo, Hangwei Qian, Ivor Tsang · PDF
  38. From Diffusion to Flow: Efficient Motion Generation in MotionGPT3

    Jaymin Ban, JiHong Jeon, SangYeop Jeong · PDF
  39. From Noise to Control: Parameterized Diffusion Policies

    Renhao Zhang, Haotian Fu, Mingxi Jia, George Konidaris, Yilun Du, Bruno Castro da Silva · PDF
  40. Full-length mRNA Design with Reward-Guided Masked Diffusion Model Fine-Tuning

    Sawan Patel, Sophia Tang, Pranam Chatterjee, Sherwood Yao · PDF
  41. Function-Space Decoupled Diffusion for Forward and Inverse Modeling in Carbon Capture and Storage

    Xin Ju, Jiachen Yao, Anima Anandkumar, Sally M Benson, Gege Wen · PDF
  42. Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control

    Zunzhe Zhang, Runhan Huang, Yicheng Liu, Shaoting Zhu, Linzhan Mou, Hang Zhao · PDF
  43. GlyphFashion: Fine-Grained Text-Aware Fashion Image Editing via Diffusion Models

    Yanting Zhang, Jingyi Guo, Huanwen Zheng, Cairong Yan, Yonggang Qi, Gaoang Wang · PDF
  44. Guess & Guide: Gradient-Free Zero-Shot Diffusion Guidance

    Abduragim Shtanchaev, Albina Ilina, Yazid Janati, Arip Asadulaev, Martin Takáč, Eric Moulines · PDF
  45. Guidance Is Not a Hyperparameter: Learning Dynamic Control in Diffusion Language Models

    Fan Zhou, Tim Van de Cruys · PDF
  46. Guided Star-Shaped Masked Diffusion

    Viacheslav Meshchaninov, Egor Shibaev, Artem Makoian, Ivan Klimov, Nikita Balagansky, Daniil Gavrilov, Aibek Alanov, Dmitry Vetrov · PDF
  47. Guided Transfer Learning for Discrete Diffusion Models

    Julian Kleutgens, Claudio Battiloro, Lingkai Kong, Benjamin F Grewe, Francesca Dominici, Mauricio Tec · PDF
  48. Hamiltonian-Guided Diffusion Fields for Variable-Length Rigid-Arm Trajectory Generation

    Guorui Sang, Pedram Rooshenas · PDF
  49. HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

    Zeyang Li, Kaveh Alim, Navid Azizan · PDF
  50. Imitation from Observations with Trajectory-Level Generative Embeddings

    Yongtao Qu, Shangzhe Li, Weitong Zhang · PDF
  51. Inference-Time Attribute Distribution Alignment for Unconditional Diffusion

    Hao Luan, See-Kiong Ng, Chun Kai Ling · PDF
  52. Inference-Time CLIP Embedding Manipulation for Compositional Text-to-Image Alignment

    Sujung Hong, Tae Eun Choi, Youngjun Jun, Chanyong Yoon, Seong Jae Hwang · PDF
  53. Learning Illumination Control in Diffusion Models

    Nishit Anand, Manan Suri, Christopher Metzler, Dinesh Manocha, Ramani Duraiswami · PDF
  54. LieFlower: Controlling Target Protein Dynamics via Lie-Guided Discrete Flows

    Manvitha Ponnapati, Tong Chen, Yinuo Zhang, Pranam Chatterjee · PDF
  55. MacroGuide: Topological Guidance for Macrocycle Generation

    Alicja Maksymiuk, Alexandre Duplessis, Michael M. Bronstein, Alexander Tong, Fernanda Duarte, Ismail Ilkan Ceylan · PDF
  56. Minimal-Action Discrete Schrödinger Bridge Matching for Peptide Sequence Design

    Shrey Goel, Pranam Chatterjee · PDF
  57. MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance

    Matina Mahdizadeh Sani, Nima Jamali, Mohammad Jalali, Farzan Farnia · PDF
  58. MolHIT: Advancing Molecular-Graph Generation with Hierarchical Discrete Diffusion Models

    Hojung Jung, Rodrigo Hormazabal, Jaehyeong Jo, Youngrok Park, Kyunggeun Roh, Se-Young Yun, Sehui Han, Dae-Woong Jeong · PDF
  59. MOOSE: Targeted Small Molecule Generation via Multi-Objective-Guided Discrete Diffusion

    Elizabeth H Mahood, William Pattie, Ethan M Jones, Sophia Vincoff, Adi Mashiach, Pranam Chatterjee · PDF
  60. Optimizing Remasking Schedules for Reasoning in Discrete Diffusion Models

    Radostin Cholakov, Zeyneb N. Kaya, Nicole H. Ma · PDF
  61. pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows

    Tong Chen, Maximilian Holsman, Lin Zhao, Yinuo Zhang, Pranam Chatterjee · PDF
  62. Protein generation with embedding learning for motif diversification

    Kevin Michalewicz, Chen Jin, Philip Alexander Teare, Tom Diethe, Mauricio Barahona, Barbara Bravi, Asher Mullokandov · PDF
  63. Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling

    Natalia Frumkin, Diana Marculescu · PDF
  64. Representation Alignment for Inverse Problems with Diffusion and Flow-Based Models

    Loukas Sfountouris, Giannis Daras, Paris Giampouras · PDF
  65. Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design

    Jaemoo Choi, Yuchen Zhu, Wei Guo, Petr Molodyk, Bo Yuan, Jinbin Bai, Yi Xin, Molei Tao, Yongxin Chen · PDF
  66. Reward-Guided Discrete Diffusion via Clean-Sample Markov Chain

    Prin Phunyaphibarn, Minhyuk Sung · PDF
  67. Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers

    Zander W. Blasingame, Chen Liu · PDF
  68. RFG: Test-Time Scaling for Diffusion Large Language Model Reasoning with Reward-Free Guidance

    Tianlang Chen, Minkai Xu, Jure Leskovec, Stefano Ermon · PDF
  69. Self-Improving Vision-Language-Action Models with Data Generation via Residual RL

    Wenli Xiao, Haotian Lin, Andy Peng, Haoru Xue, Tairan He, Zhengyi Luo, Yuqi Xie, Fengyuan Hu, Linxi Fan, Guanya Shi, Yuke Zhu · PDF
  70. Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions

    Van Khoa Nguyen, Lionel Blondé, Alexandros Kalousis · PDF
  71. Stochastic Few-step Models

    Romeo Passaro, Zander W. Blasingame, Michael M. Bronstein, Alexander Tong · PDF
  72. Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models

    Seunghwan Jang, SooJean Han · PDF
  73. TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation

    Hanqun Cao, Aastha Pal, Sophia Tang, Yinuo Zhang, Jingjie Zhang, Pheng-Ann Heng, Pranam Chatterjee · PDF
  74. Time-to-Move: Training-Free Motion-Controlled Video Generation via Dual-Clock Denoising

    Assaf Singer, Noam Rotstein, Amir Mann, Ron Kimmel, Or Litany · PDF
  75. Trust-Region Noise Search for Black-Box Alignment of Diffusion and Flow Models

    Niklas Schweiger, Karnik Ram, Daniel Cremers · PDF
  76. Understanding Sampler Stochasticity in Training Diffusion Models for RLHF

    Jiayuan Sheng, Hanyang Zhao, Haoxian Chen, David Yao, Wenpin Tang · PDF
  77. Unifying Autoregressive and Discrete Diffusion Language Modeling via Cross-Regressive Decoding

    Dmitry Abulkhanov, Daniil Strizhakov, Maxim Panov · PDF
  78. UniGuide: Learning Guidance Policies for Multi-Objective Diffusion Sampling

    Mahmoud Hegazy, Navid Bagheri Shouraki, Eric Moulines, Aymeric Dieuleveut, Michael I. Jordan, Yazid Janati · PDF
  79. Variational Entropic Optimal Transport

    Roman Dyachenko, Nikita Gushchin, Kirill Sokolov, Petr Mokrov, Evgeny Burnaev, Alexander Korotin · PDF
  80. Verifier-Threshold: An Efficient Test-Time Scaling Approach for Image Generation

    Vignesh Sundaresha, Akash Haridas, Vikram Appia, Lav R. Varshney · PDF
  81. When Guidance Breaks: A Schrödinger Bridge Perspective on Inference-Time Alignment in Diffusion Models

    Mahule Roy, Subhas Roy · PDF
  82. When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance

    Ahmed Ghorbel, Badr MOUFAD, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati · PDF
  83. Where and How to Perturb: On the Design of Perturbation Guidance in Diffusion and Flow Models

    Donghoon Ahn, Jiwon Kang, Sanghyun Lee, Minjae Kim, Jaewon Min, Wooseok Jang, Sangwu Lee, Sayak Paul, Susung Hong, Seungryong Kim · PDF
  84. WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling

    Michael Aich, Andreas Fürst, Florian Sestak, Carlos Ruiz-Gonzalez, Niklas Boers, Johannes Brandstetter · PDF