mlsanityData to 7 Oct 2026

Improving GFlowNets with Monte Carlo Tree Search

arXiv 2406.13655 ↗First posted 19 Jun 2024cs.LG cs.AIcited by 8

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Abstract (arXiv)

Generative Flow Networks (GFlowNets) treat sampling from distributions over compositional discrete spaces as a sequential decision-making problem, training a stochastic policy to construct objects step by step. Recent studies have revealed strong connections between GFlowNets and entropy-regularized reinforcement learning. Building on these insights, we propose to enhance planning capabilities of GFlowNets by applying Monte Carlo Tree Search (MCTS). Specifically, we show how the MENTS algorithm (Xiao et al., 2019) can be adapted for GFlowNets and used during both training and inference. Our experiments demonstrate that this approach improves the sample efficiency of GFlowNet training and the generation fidelity of pre-trained GFlowNet models.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 20 of its 30 references that are in the map. First posted on arXiv 19 Jun 2024.

Builds on

20 of 30 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  4. 2019Mastering Atari, Go, Chess and Shogi by Planning with a Learned Modelcited by 1,327
  5. 2017Reinforcement Learning with Deep Energy-Based Policiescited by 659
  6. 2021Flow Network based Generative Models for Non-Iterative Diverse Candidate Generationcited by 384
  7. 2021GFlowNet Foundationscited by 286
  8. 2019A Theory of Regularized Markov Decision Processescited by 279
  9. 2022Trajectory balance: Improved credit assignment in GFlowNetscited by 244
  10. 2017A unified view of entropy-regularized Markov decision processescited by 174
  11. 2017Equivalence Between Policy Gradients and Soft Q-Learningcited by 172
  12. 2022Biological Sequence Design with GFlowNetscited by 172
8 more
  1. 2022Learning GFlowNets from partial episodes for improved convergence and stabilitycited by 129
  2. 2023Amortizing intractable inference in large language modelscited by 94
  3. 2023GFlowNets for AI-Driven Scientific Discoverycited by 63
  4. 2023Generative Flow Networks as Entropy-Regularized RLcited by 60
  5. 2024Discrete Probabilistic Inference as Control in Multi-path Environmentscited by 40
  6. 2023Maximum entropy GFlowNets with soft Q-learningcited by 30
  7. 2023DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNetscited by 27
  8. 2023Order-Preserving GFlowNetscited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 3.

8 papers.

  1. 2025Diffusion Tree Sampling: Scalable inference-time alignment of diffusion modelscited by 31
  2. 2024Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximizationcited by 12
  3. 2025Revisiting Non-Acyclic GFlowNets in Discrete Environmentscited by 8
  4. 2025Reinforced sequential Monte Carlo for amortised samplingcited by 5
  5. 2025gfnx: Fast and Scalable Library for Generative Flow Networks in JAXcited by 2
  6. 2026Rooted Absorbed Prefix Trajectory Balance with Submodular Replay for GFlowNet Trainingcited by 2
  7. 2026Learning Shortest Paths with Generative Flow Networkscited by 2
  8. 2026Your GFlowNet Secretly Learns an Optimal Transport Plancited by 0