{"total":31,"rows":[{"id":"2310.02679","title":"Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization","created":"2023-10-04","cited_by_count":57,"area":null},{"id":"2403.07041","title":"Ant Colony Sampling with GFlowNets for Combinatorial Optimization","created":"2024-03-11","cited_by_count":53,"area":null},{"id":"2310.02710","title":"Local Search GFlowNets","created":"2023-10-04","cited_by_count":48,"area":null},{"id":"2402.10309","title":"Discrete Probabilistic Inference as Control in Multi-path Environments","created":"2024-02-15","cited_by_count":44,"area":null},{"id":"2310.02823","title":"Learning to Scale Logits for Temperature-Conditional GFlowNets","created":"2023-10-04","cited_by_count":27,"area":null},{"id":"2310.03301","title":"Learning Energy Decompositions for Partial Inference of GFlowNets","created":"2023-10-05","cited_by_count":24,"area":null},{"id":"2311.14156","title":"Variational Annealing on Graphs for Combinatorial Optimization","created":"2023-11-23","cited_by_count":21,"area":null},{"id":"2310.03419","title":"Pre-Training and Fine-Tuning Generative Flow Networks","created":"2023-10-05","cited_by_count":17,"area":null},{"id":"2402.10705","title":"AutoSAT: Automatically Optimize SAT Solvers via Large Language Models","created":"2024-02-16","cited_by_count":15,"area":null},{"id":"2502.17100","title":"Generative Models in Decision Making: A Survey","created":"2025-02-24","cited_by_count":15,"area":null},{"id":"2310.00386","title":"Order-Preserving GFlowNets","created":"2023-09-30","cited_by_count":13,"area":null},{"id":"2312.15246","title":"A Theory of Non-Acyclic Generative Flow Networks","created":"2023-12-23","cited_by_count":12,"area":null},{"id":"2310.00526","title":"Are Graph Neural Networks Optimal Approximation Algorithms?","created":"2023-10-01","cited_by_count":11,"area":null},{"id":"2405.08424","title":"Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More","created":"2024-05-14","cited_by_count":7,"area":null},{"id":"2406.05426","title":"Baking Symmetry into GFlowNets","created":"2024-06-08","cited_by_count":7,"area":null},{"id":"2407.20806","title":"ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning","created":"2024-07-30","cited_by_count":7,"area":null},{"id":"2410.09355","title":"On Divergence Measures for Training GFlowNets","created":"2024-10-12","cited_by_count":6,"area":null},{"id":"2411.05899","title":"Streaming Bayes GFlowNets","created":"2024-11-08","cited_by_count":4,"area":null},{"id":"2602.17827","title":"Avoid What You Know: Divergent Trajectory Balance for GFlowNets","created":"2026-02-19","cited_by_count":4,"area":null},{"id":"2406.03288","title":"Embarrassingly Parallel GFlowNets","created":"2024-06-05","cited_by_count":3,"area":null},{"id":"2406.11897","title":"A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial Optimization","created":"2024-06-14","cited_by_count":3,"area":null},{"id":"2601.17582","title":"GenAI-Net: A Generative AI Framework for Automated Biomolecular Network Design","created":"2026-01-24","cited_by_count":2,"area":null},{"id":"2602.08210","title":"CADO: From Imitation to Cost Minimization for Heatmap-based Solvers in Combinatorial Optimization","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2603.03045","title":"QFlowNet: Fast, Diverse, and Efficient Unitary Synthesis with Generative Flow Networks","created":"2026-03-03","cited_by_count":1,"area":null},{"id":"2511.19573","title":"Neural Tractability via Structure: Learning-Augmented Algorithms for Graph Combinatorial Optimization","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2602.00302","title":"Neural Ising Machines via Unrolling and Zeroth-Order Training","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2603.02462","title":"Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2603.06260","title":"Learning to Solve Orienteering Problem with Time Windows and Variable Profits","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2604.23921","title":"Crystal structure prediction using graph neural combinatorial optimization","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2608.08644","title":"Path-dependent Discrete Amortized Inference","created":"2026-08-09","cited_by_count":0,"area":null},{"id":"2609.11538","title":"Particle GFlowNets: Rethinking Generative Marginalization Models","created":"2026-09-10","cited_by_count":0,"area":null}],"next_cursor":null}