FALCON: Few-step Accurate Likelihoods for Continuous Flows
Fuente:
arXiv
Saved in:
| Main Authors: | Rehman, Danyal, Akhound-Sadegh, Tara, Gazizov, Artem, Bengio, Yoshua, Tong, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators
by: Rehman, Danyal, et al.
Published: (2025)
by: Rehman, Danyal, et al.
Published: (2025)
Trajectory Flow Matching with Applications to Clinical Time Series Modeling
by: Zhang, Xi, et al.
Published: (2024)
by: Zhang, Xi, et al.
Published: (2024)
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
by: Bose, Avishek Joey, et al.
Published: (2023)
by: Bose, Avishek Joey, et al.
Published: (2023)
Distributional GFlowNets with Quantile Flows
by: Zhang, Dinghuai, et al.
Published: (2023)
by: Zhang, Dinghuai, et al.
Published: (2023)
In-Context Parametric Inference: Point or Distribution Estimators?
by: Mittal, Sarthak, et al.
Published: (2025)
by: Mittal, Sarthak, et al.
Published: (2025)
GFlowNet Foundations
by: Bengio, Yoshua, et al.
Published: (2021)
by: Bengio, Yoshua, et al.
Published: (2021)
Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
by: Akhound-Sadegh, Tara, et al.
Published: (2025)
by: Akhound-Sadegh, Tara, et al.
Published: (2025)
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
by: Zhang, Dinghuai, et al.
Published: (2023)
by: Zhang, Dinghuai, et al.
Published: (2023)
Monte Carlo Tree Diffusion for System 2 Planning
by: Yoon, Jaesik, et al.
Published: (2025)
by: Yoon, Jaesik, et al.
Published: (2025)
Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control
by: Jiralerspong, Thomas, et al.
Published: (2025)
by: Jiralerspong, Thomas, et al.
Published: (2025)
In-Context Reinforcement Learning through Bayesian Fusion of Context and Value Prior
by: Berkes, Anaïs, et al.
Published: (2026)
by: Berkes, Anaïs, et al.
Published: (2026)
A Complexity-Based Theory of Compositionality
by: Elmoznino, Eric, et al.
Published: (2024)
by: Elmoznino, Eric, et al.
Published: (2024)
Were RNNs All We Needed?
by: Feng, Leo, et al.
Published: (2024)
by: Feng, Leo, et al.
Published: (2024)
Efficient Causal Graph Discovery Using Large Language Models
by: Jiralerspong, Thomas, et al.
Published: (2024)
by: Jiralerspong, Thomas, et al.
Published: (2024)
Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization
by: Liu, Shengchao, et al.
Published: (2025)
by: Liu, Shengchao, et al.
Published: (2025)
Active Attacks: Red-teaming LLMs via Adaptive Environments
by: Yun, Taeyoung, et al.
Published: (2025)
by: Yun, Taeyoung, et al.
Published: (2025)
Sampling from Energy-based Policies using Diffusion
by: Jain, Vineet, et al.
Published: (2024)
by: Jain, Vineet, et al.
Published: (2024)
Discrete, compositional, and symbolic representations through attractor dynamics
by: Nam, Andrew, et al.
Published: (2023)
by: Nam, Andrew, et al.
Published: (2023)
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
by: Zhao, Mingde, et al.
Published: (2023)
by: Zhao, Mingde, et al.
Published: (2023)
Action abstractions for amortized sampling
by: Boussif, Oussama, et al.
Published: (2024)
by: Boussif, Oussama, et al.
Published: (2024)
Mitigating Shortcut Learning with Diffusion Counterfactuals and Diverse Ensembles
by: Scimeca, Luca, et al.
Published: (2023)
by: Scimeca, Luca, et al.
Published: (2023)
Structure-Aligned Protein Language Model
by: Chen, Can, et al.
Published: (2025)
by: Chen, Can, et al.
Published: (2025)
Learning What Matters: Steering Diffusion via Spectrally Anisotropic Forward Noise
by: Scimeca, Luca, et al.
Published: (2025)
by: Scimeca, Luca, et al.
Published: (2025)
Adaptive Inference-Time Scaling via Cyclic Diffusion Search
by: Lee, Gyubin, et al.
Published: (2025)
by: Lee, Gyubin, et al.
Published: (2025)
Unlearning via Sparse Representations
by: Shah, Vedant, et al.
Published: (2023)
by: Shah, Vedant, et al.
Published: (2023)
Local Inconsistency Resolution: The Interplay between Attention and Control in Probabilistic Models
by: Richardson, Oliver E., et al.
Published: (2026)
by: Richardson, Oliver E., et al.
Published: (2026)
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction
by: Rector-Brooks, Jarrid, et al.
Published: (2024)
by: Rector-Brooks, Jarrid, et al.
Published: (2024)
Discrete Feynman-Kac Correctors
by: Hasan, Mohsin, et al.
Published: (2026)
by: Hasan, Mohsin, et al.
Published: (2026)
Geometric Signatures of Compositionality Across a Language Model's Lifetime
by: Lee, Jin Hwa, et al.
Published: (2024)
by: Lee, Jin Hwa, et al.
Published: (2024)
Latent Veracity Inference for Identifying Errors in Stepwise Reasoning
by: Kim, Minsu, et al.
Published: (2025)
by: Kim, Minsu, et al.
Published: (2025)
Self-Evolving Curriculum for LLM Reasoning
by: Chen, Xiaoyin, et al.
Published: (2025)
by: Chen, Xiaoyin, et al.
Published: (2025)
On Continuity of Robust and Accurate Classifiers
by: Barati, Ramin, et al.
Published: (2023)
by: Barati, Ramin, et al.
Published: (2023)
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery
by: Teng, Mélisande, et al.
Published: (2025)
by: Teng, Mélisande, et al.
Published: (2025)
When 2D Tasks Meet 1D Serialization: On Serialization Friction in Structured Tasks
by: Lo, Chung-Hsiang, et al.
Published: (2026)
by: Lo, Chung-Hsiang, et al.
Published: (2026)
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity
by: Williams-King, David, et al.
Published: (2025)
by: Williams-King, David, et al.
Published: (2025)
Mitigating the Likelihood Paradox in Flow-based OOD Detection via Entropy Manipulation
by: Kim, Donghwan, et al.
Published: (2026)
by: Kim, Donghwan, et al.
Published: (2026)
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving
by: Didolkar, Aniket, et al.
Published: (2024)
by: Didolkar, Aniket, et al.
Published: (2024)
Machine learning and information theory concepts towards an AI Mathematician
by: Bengio, Yoshua, et al.
Published: (2024)
by: Bengio, Yoshua, et al.
Published: (2024)
Accurate Forgetting for Heterogeneous Federated Continual Learning
by: Wuerkaixi, Abudukelimu, et al.
Published: (2025)
by: Wuerkaixi, Abudukelimu, et al.
Published: (2025)
Similar Items
-
Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators
by: Rehman, Danyal, et al.
Published: (2025) -
Trajectory Flow Matching with Applications to Clinical Time Series Modeling
by: Zhang, Xi, et al.
Published: (2024) -
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
by: Bose, Avishek Joey, et al.
Published: (2023) -
Distributional GFlowNets with Quantile Flows
by: Zhang, Dinghuai, et al.
Published: (2023) -
In-Context Parametric Inference: Point or Distribution Estimators?
by: Mittal, Sarthak, et al.
Published: (2025)