Evolution Guided Generative Flow Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Ikram, Zarif, Pan, Ling, Liu, Dianbo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Masked Generative Priors Improve World Models Sequence Modelling Capabilities
by: Meo, Cristian, et al.
Published: (2024)
by: Meo, Cristian, et al.
Published: (2024)
Performance Asymmetry in Model-Based Reinforcement Learning
by: Lim, Jing Yu, et al.
Published: (2025)
by: Lim, Jing Yu, et al.
Published: (2025)
CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
by: Ikram, Zarif, et al.
Published: (2026)
by: Ikram, Zarif, et al.
Published: (2026)
Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models
by: Wu, Yudi, et al.
Published: (2025)
by: Wu, Yudi, et al.
Published: (2025)
Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities
by: Xie, Ziwen, et al.
Published: (2026)
by: Xie, Ziwen, et al.
Published: (2026)
SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation
by: Vetcha, Nitin, et al.
Published: (2026)
by: Vetcha, Nitin, et al.
Published: (2026)
Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
by: Sinha, Abhijeet, et al.
Published: (2026)
by: Sinha, Abhijeet, et al.
Published: (2026)
Bifurcated Generative Flow Networks
by: Li, Chunhui, et al.
Published: (2024)
by: Li, Chunhui, et al.
Published: (2024)
Auto-Discovery-Bench: Diagnosing Structured State Tracking in Oracle-Guided Discovery
by: Chen, Tingting, et al.
Published: (2025)
by: Chen, Tingting, et al.
Published: (2025)
Representation Collapsing Problems in Vector Quantization
by: Zhao, Wenhao, et al.
Published: (2024)
by: Zhao, Wenhao, et al.
Published: (2024)
STORI: A Benchmark and Taxonomy for Stochastic Environments
by: Barsainyan, Aryan Amit, et al.
Published: (2025)
by: Barsainyan, Aryan Amit, et al.
Published: (2025)
Improving Discrete Optimisation Via Decoupled Straight-Through Estimator
by: Shah, Rushi, et al.
Published: (2024)
by: Shah, Rushi, et al.
Published: (2024)
VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism
by: Wu, Jiawei, et al.
Published: (2024)
by: Wu, Jiawei, et al.
Published: (2024)
Generative Modeling with Flow-Guided Density Ratio Learning
by: Heng, Alvin, et al.
Published: (2023)
by: Heng, Alvin, et al.
Published: (2023)
General Proximal Flow Networks
by: Strunk, Alexander, et al.
Published: (2026)
by: Strunk, Alexander, et al.
Published: (2026)
Absurd World: A Simple Yet Powerful Method to Absurdify the Real-world for Probing LLM Reasoning Capabilities
by: Albright, Ryan, et al.
Published: (2026)
by: Albright, Ryan, et al.
Published: (2026)
TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency
by: Imteaj, Ahmed, et al.
Published: (2024)
by: Imteaj, Ahmed, et al.
Published: (2024)
Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers
by: Saxena, Krati, et al.
Published: (2025)
by: Saxena, Krati, et al.
Published: (2025)
Path-Guided Flow Matching for Dataset Distillation
by: Li, Xuhui, et al.
Published: (2026)
by: Li, Xuhui, et al.
Published: (2026)
Learning Shortest Paths with Generative Flow Networks
by: Morozov, Nikita, et al.
Published: (2026)
by: Morozov, Nikita, et al.
Published: (2026)
Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization
by: Zhao, Wenhao, et al.
Published: (2026)
by: Zhao, Wenhao, et al.
Published: (2026)
Training Free Guided Flow Matching with Optimal Control
by: Wang, Luran, et al.
Published: (2024)
by: Wang, Luran, et al.
Published: (2024)
Let Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation
by: Verma, Yogesh, et al.
Published: (2025)
by: Verma, Yogesh, et al.
Published: (2025)
Distributional GFlowNets with Quantile Flows
by: Zhang, Dinghuai, et al.
Published: (2023)
by: Zhang, Dinghuai, et al.
Published: (2023)
Neural Network Optimal Power Flow via Energy Gradient Flow and Unified Dynamics
by: Liu, Xuezhi
Published: (2025)
by: Liu, Xuezhi
Published: (2025)
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2024)
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2024)
Energy Guided Geometric Flow Matching
by: Zweig, Aaron, et al.
Published: (2025)
by: Zweig, Aaron, et al.
Published: (2025)
Gradient Flow Convergence Guarantee for General Neural Network Architectures
by: Jakhmola, Yash
Published: (2025)
by: Jakhmola, Yash
Published: (2025)
Adversarial Generative Flow Network for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)
by: Zhang, Ni, et al.
Published: (2025)
Towards Generalization of Graph Neural Networks for AC Optimal Power Flow
by: Arowolo, Olayiwola, et al.
Published: (2025)
by: Arowolo, Olayiwola, et al.
Published: (2025)
Boolean Product Graph Neural Networks
by: Wang, Ziyan, et al.
Published: (2024)
by: Wang, Ziyan, et al.
Published: (2024)
Laplacian Score Sharpening for Mitigating Hallucination in Diffusion Models
by: C, Barath Chandran., et al.
Published: (2025)
by: C, Barath Chandran., et al.
Published: (2025)
Gradients Must Earn Their Influence: Unifying SFT with Generalized Entropic Objectives
by: Wang, Zecheng, et al.
Published: (2026)
by: Wang, Zecheng, et al.
Published: (2026)
Bayesian Flow Networks
by: Graves, Alex, et al.
Published: (2023)
by: Graves, Alex, et al.
Published: (2023)
Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences
by: Cao, Jiarui, et al.
Published: (2026)
by: Cao, Jiarui, et al.
Published: (2026)
How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance
by: Huang, Jerry Y., et al.
Published: (2026)
by: Huang, Jerry Y., et al.
Published: (2026)
MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data
by: Ling, Yaobin, et al.
Published: (2024)
by: Ling, Yaobin, et al.
Published: (2024)
Flow to Learn: Flow Matching on Neural Network Parameters
by: Saragih, Daniel, et al.
Published: (2025)
by: Saragih, Daniel, et al.
Published: (2025)
Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
by: Yang, Yu, et al.
Published: (2026)
by: Yang, Yu, et al.
Published: (2026)
Greed is Good: A Unifying Perspective on Guided Generation
by: Blasingame, Zander W., et al.
Published: (2025)
by: Blasingame, Zander W., et al.
Published: (2025)
Similar Items
-
Masked Generative Priors Improve World Models Sequence Modelling Capabilities
by: Meo, Cristian, et al.
Published: (2024) -
Performance Asymmetry in Model-Based Reinforcement Learning
by: Lim, Jing Yu, et al.
Published: (2025) -
CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
by: Ikram, Zarif, et al.
Published: (2026) -
Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models
by: Wu, Yudi, et al.
Published: (2025) -
Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities
by: Xie, Ziwen, et al.
Published: (2026)