Generative Flow Networks

Also known as GFlowNet

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8 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

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Learning a Mixture of GFlowNets
Oct 6, 2026Tiago da Silva, Amauri H. Souza, Salem LahlouGenerative Flow Networks
MBZUAI, UAE · Avra, Brazil & Federal Institute of Cear´a, Brazil
Universality and Convergence of Generative Flows
Oct 4, 2026Leo BrunswicFlow Matching Generative Flow Networks
LLM Suite Team, JP Morgan Chase & Co.
Beyond Mode Collapse: Generating Diverse Synthetic Expert Conversations via Generative Flow Networks
Sep 29, 2026Sumit Asthana, Michael Ion, Kevyn Collins ThompsonGenerative Flow Networks Flow-Based Generative Modeling
University of Michigan Ann Arbor, MI, USA
FlowMap-OPD: Rollout--Kernel Separation for On-Policy Distillation of Few-Step Flow-Map Generators
Sep 29, 2026Zhiqi Li, Bo ZhuGenerative Flow Networks Flow Map Learning
Georgia Institute of Technology
One Proposal for Every Margin: Zero-Shot Amortized Sequential Importance Sampling for Binary Matrices
Sep 28, 2026Ruishuo Chen, Weijia Li, Xun Wang +3Importance Sampling Generative Flow Networks
Institute for Interdisciplinary Information Sciences, Tsinghua University · Department of Statistics and Data Science, Tsinghua University
CapField-OPD: Learning Continuous Capability Fields via Joint-Anchored Multi-Teacher On-Policy Distillation for Flow Models
Sep 28, 2026Pengyang Ling, Jiazi Bu, Yujie Zhou +6Generative Flow Networks Multi-Teacher Knowledge Distillation
University of Science and Technology of China · Shanghai Jiao Tong University · Fudan University +2
R $^2$ Flow: Recursive Self-Improvement via Recursive Skill Evolution
Sep 27, 2026Mingda Zhang, Qiang Huang, Yanjin Li +4LLM Agent Self-Improvement Generative Flow Networks
The Chinese University of Hong Kong, Shenzhen · Fudan University · University of Illinois at Urbana-Champaign +2
WTF?! Simulation-Free Reinforcement Learning with Wasserstein-Tilted Flow Maps
Sep 22, 2026Abbas Mammadov, Jerry Y. Huang, Justin Lin +5Reinforcement Learning Generative Flow Networks
University of Oxford · Carnegie Mellon University
Particle GFlowNets: Rethinking Generative Marginalization Models
Sep 11, 2026Tiago da Silva, Diego Mesquita, Salem LahlouMarkov Chain Monte Carlo Generative Flow Networks
MBZUAI · School of Applied Mathematics, Getulio Vargas Foundation
CrystalGRPO: Target-Aligned and Coverage-Preserving Reinforcement Learning for Flow-Based Crystal Structure Prediction
Aug 6, 2026Kaixiang Su, Hongfei Xue, Qiang ZhuCrystal Structure Prediction Group Relative Policy Optimization
Department of Computer Science, University of North Carolina at Charlotte · Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte · North Carolina Battery Complexity, Autonomous Vehicle and Electrification (BATT CAVE) Research Center
IFlowNets: Extending Generative Samplers to Learn Strategies in Incomplete Information Games
Aug 5, 2026Conor M. Artman, Nicholas Di, Scott PerkinsImperfect-Information Games Generative Flow Networks
AI Research Group, Lawrence Livermore National Laboratory · Deptartment of Statistics, Rice University · Strategic Competition Analysis Group, Lawrence Livermore National Laboratory
Information-Geometric Forward Policy Training in GFlowNets
Aug 4, 2026Yordan Raykov, Rodrigo VeigaInformation Geometry Natural Gradient Methods
School of Mathematical Sciences, University of Nottingham, Nottingham, UK
AlphaG-OPD: Reliability-Gated Sibling Counterfactuals for On-Policy Distillation in Symbolic Alpha Factor Discovery
Aug 2, 2026Yaoyu SuQuantitative Finance Generative Flow Networks
GFlowRL: Scaling Distribution-Matching RL to Large Language Models
Jul 15, 2026Xiaodong Liu, Michael Xu, Jack W. Stokes +3RL for Code Generation Reinforcement Learning
Microsoft Research
Self-conditioned Flow Map Language Models via Fixed-point Flows
Jul 1, 2026Jaehoon Yoo, Wonjung Kim, Floor Eijkelboom +4Normalizing Flows One-Step Generative Modeling
KAIST · University of Amsterdam · Carnegie Mellon University
Posterior Refinement: Fast Language Generation via Any-Order Flow Maps
Jun 23, 2026Manan Agarwal, Sheel Shah, Chanhyuk Lee +6Non-Autoregressive Text Generation Generative Flow Networks
Carnegie Mellon University · KAIST
FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction
Jun 23, 2026Kunyu Ni, Lei Cao, Jie He +4Generative Flow Networks Flow-Based Generative Modeling
Ocean University of China China · University of Arizona USA · University of Science and Technology Beijing China +1
Latent Thought Flow: Efficient Latent Reasoning in Large Language Models
Jun 15, 2026Xiandong Zou, Jing Huang, Jianshu Li +1RL for Language Model Reasoning Efficient Language Model Reasoning
Singapore Management University · Ant Group
Proximal Policy Optimization for Amortized Discrete Sampling
Jun 14, 2026Anna Zykova-Myzina, Timofei Gritsaev, Daniil Tiapkin +1Molecular Graph Generation Generative Flow Networks
HSE University · Constructor University · CMAP, CNRS, École polytechnique, IPP
Flow-based Policy Adaptation without Policy Updates
Jun 4, 2026Luzhe Sun, Jingtian Ji, Haoran Chen +2Robot Policy Learning Robot Policy Adaptation
Toyota Technological Institute at Chicago · Stony Brook University
Your GFlowNet Secretly Learns an Optimal Transport Plan
Jun 4, 2026Ian Maksimov, Nikita Morozov, Denis Belomestny +1Generative Flow Networks Flow-Based Generative Modeling
1HSE University · 2Duisburg-Essen University
Scalable Inference-Time Annealing with Surrogate Likelihood Estimators
May 29, 2026Daniel Peñaherrera, Rishal Aggarwal, David Ryan KoesGenerative Flow Networks
CMU-Pitt PhD Program in Computational Biology · Dept. of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
Conflict-Aware Additive Guidance for Flow Models under Compositional Rewards
May 20, 2026Xuehui Yu, Fucheng Cai, Meiyi Wang +2Constrained Generative Modeling Diffusion Model Guidance
Smart Systems Institute, National University of Singapore, Singapore · Faculty of Computing, Harbin Institute of Technology, Harbin, China · School of Computing, National University of Singapore, Singapore
Distribution Matching Distillation without Fake Score Network
May 19, 2026Youngjoong Kim, Deokyeong Lee, Jaesik ParkDiffusion Model Distillation Few-Step Diffusion Sampling
Department of Computer Science and Engineering, Seoul National University · Department of Computer Science and Engineering, Sogang University Seoul, Republic of Korea
CAB: Accelerating Flow and Diffusion Sampling via Rectification and Corrected Adams-Bashforth
May 16, 2026Anuska Roy, Pravin NairFew-Step Diffusion Sampling Generative Flow Networks
Department of Electrical Engineering Indian Institute of Technology Madras, Chennai, India
$f$ -Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
May 14, 2026Jake Fawkes, Jason HartfordGenerative Flow Networks Variational Inference
Department of Statistics, University College London, UK · Valence Labs, London, UK · Recursion, London, UK.
SkillFlow: Flow-Driven Recursive Skill Evolution for Agentic Orchestration
May 13, 2026Mingda Zhang, Tiesunlong Shen, Haoran Luo +4LLM Agent Orchestration LLM Agent Self-Improvement
The Chinese University of Hong Kong, Shenzhen · National University of Singapore · Nanyang Technological University +1
Restoration-Aligned Generative Flow Models for Blind Motion Deblurring
May 9, 2026Insoo Kim, Jinwoo ShinFlow Matching Image Deblurring
1NAVER Cloud · 2KAIST AI
Conservative Flows: A New Paradigm of Generative Models
May 7, 2026Eshed Gal, Md Shahriar Rahim Siddiqui, Moshe Eliasof +1Langevin Dynamics Generative Flow Networks
The University of British Columbia Vancouver, Canada · University of Cambridge Cambridge, United Kingdom
Stable GFlowNets with Probabilistic Guarantees
May 3, 2026Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal +6Generative Flow Networks Flow-Based Generative Modeling
Lyles School of Civil and Construction Engineering, Purdue University, IN, USA · Department of Computer Science, Purdue University, IN, USA · Computer Science and Engineering, University of California, Santa Cruz, USA

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

Learning a Mixture of GFlowNets

Tiago da Silva, Amauri H. Souza, Salem Lahlou

MBZUAI, UAE · Avra, Brazil & Federal Institute of Cear´a, Brazil

Generative Flow Networks

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Learning an ensemble of GFlowNets to sample from a discrete target distribution has become a common approach for achieving better state space exploration and convergence than that of a monolithic sampler. However, these methods often add a substantial runtime overhead to the base model, and their conceptual connection remains elusive. To address this, we first propose a general-purpose theoretical framework for describing a mixture of GFlowNets, which we specialize into continuously (CI) and discretely indexed (DI) collections. On the one hand, we show CI GFlowNets can be interpreted through the lens of a random features expansion, provably boosting the sampler's expressivity in graph-structured tasks and reducing learning instability via spectral shifting. On the other hand, we demonstrate DI GFlowNets encompass prior approaches for GFlowNet training and provide the foundation for the newly proposed Stratum-Conditioned (SC) GFlowNets. This method, which is inspired by the Doob's h-transform of Markov chains, decomposes the state space according to a prescribed modular function and restricts each component to sample from a distinct subset of it. Importantly, SC GFlowNets support centralized and component-wise embarrassingly parallel training, and we show both of them significantly speed up learning convergence and mode coverage without introducing any non-negligible extra computation.

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