Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training.
CoRR, March, 2025
Solving Bayesian inverse problems with diffusion priors and off-policy RL.
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CoRR, March, 2025
Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning.
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Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Action abstractions for amortized sampling.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Multi-Fidelity Active Learning with GFlowNets.
Trans. Mach. Learn. Res., 2024
Proof Flow: Preliminary Study on Generative Flow Network Language Model Tuning for Formal Reasoning.
CoRR, 2024
Automated Discovery of Pairwise Interactions from Unstructured Data.
CoRR, 2024
Towards DNA-Encoded Library Generation with GFlowNets.
CoRR, 2024
Amortizing intractable inference in diffusion models for vision, language, and control.
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
PhyloGFN: Phylogenetic inference with generative flow networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Pre-Training and Fine-Tuning Generative Flow Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Amortizing intractable inference in large language models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
DEUP: Direct Epistemic Uncertainty Prediction.
Trans. Mach. Learn. Res., 2023
Thompson sampling for improved exploration in GFlowNets.
CoRR, 2023
BatchGFN: Generative Flow Networks for Batch Active Learning.
CoRR, 2023
GFlowNets for AI-Driven Scientific Discovery.
CoRR, 2023
Stochastic Generative Flow Networks.
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability.
Proceedings of the International Conference on Machine Learning, 2023
GFlowOut: Dropout with Generative Flow Networks.
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Proceedings of the International Conference on Machine Learning, 2023
Multi-Objective GFlowNets.
Proceedings of the International Conference on Machine Learning, 2023
GFlowNet-EM for Learning Compositional Latent Variable Models.
Proceedings of the International Conference on Machine Learning, 2023
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions.
CoRR, 2022
Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection.
CoRR, 2022
Trajectory balance: Improved credit assignment in GFlowNets.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Biological Sequence Design with GFlowNets.
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Proceedings of the International Conference on Machine Learning, 2022
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
DROCC: Deep Robust One-Class Classification.
Proceedings of the 37th International Conference on Machine Learning, 2020
Improving Convergence in IRGAN with PPO.
Proceedings of the CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, 2020
Proximal Policy Optimization for Improved Convergence in IRGAN.
CoRR, 2019