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2503.19385
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Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing
25 March 2025
Jaihoon Kim
Taehoon Yoon
Jisung Hwang
Minhyuk Sung
DiffM
Re-assign community
ArXiv (abs)
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HuggingFace (34 upvotes)
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Papers citing
"Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing"
21 / 71 papers shown
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
M. S. Albergo
Nicholas M. Boffi
Eric Vanden-Eijnden
DiffM
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562
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15 Mar 2023
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
European Conference on Computer Vision (ECCV), 2023
Shilong Liu
Zhaoyang Zeng
Tianhe Ren
Feng Li
Hao Zhang
...
Chun-yue Li
Jianwei Yang
Hang Su
Jun Zhu
Lei Zhang
ObjD
775
3,281
0
09 Mar 2023
Universal Guidance for Diffusion Models
Arpit Bansal
Hong-Min Chu
Avi Schwarzschild
Soumyadip Sengupta
Micah Goldblum
Jonas Geiping
Tom Goldstein
VLM
265
376
0
14 Feb 2023
Flow Matching for Generative Modeling
International Conference on Learning Representations (ICLR), 2022
Y. Lipman
Ricky T. Q. Chen
Heli Ben-Hamu
Maximilian Nickel
Matt Le
OOD
1.1K
2,869
0
06 Oct 2022
Diffusion Posterior Sampling for General Noisy Inverse Problems
International Conference on Learning Representations (ICLR), 2022
Hyungjin Chung
Jeongsol Kim
Michael T. McCann
M. Klasky
J. C. Ye
DiffM
634
1,242
0
29 Sep 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
International Conference on Learning Representations (ICLR), 2022
Xingchao Liu
Chengyue Gong
Qiang Liu
OOD
1.1K
2,003
0
07 Sep 2022
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
Neural Information Processing Systems (NeurIPS), 2022
Cheng Lu
Yuhao Zhou
Fan Bao
Jianfei Chen
Chongxuan Li
Jun Zhu
DiffM
750
1,956
0
02 Jun 2022
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting
Neural Information Processing Systems (NeurIPS), 2022
Tomasz Korbak
Hady ElSahar
Germán Kruszewski
Marc Dymetman
CLL
296
75
0
01 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models
Neural Information Processing Systems (NeurIPS), 2022
Tero Karras
M. Aittala
Timo Aila
S. Laine
DiffM
909
2,746
0
01 Jun 2022
High-Resolution Image Synthesis with Latent Diffusion Models
Computer Vision and Pattern Recognition (CVPR), 2021
Robin Rombach
A. Blattmann
Dominik Lorenz
Patrick Esser
Bjorn Ommer
DiffM
3.0K
21,096
0
20 Dec 2021
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng
Yutong He
Yang Song
Jiaming Song
Jiajun Wu
Jun-Yan Zhu
Stefano Ermon
DiffM
588
1,907
0
02 Aug 2021
Variational Diffusion Models
Diederik P. Kingma
Tim Salimans
Ben Poole
Jonathan Ho
DiffM
880
1,353
0
01 Jul 2021
Diffusion Models Beat GANs on Image Synthesis
Neural Information Processing Systems (NeurIPS), 2021
Prafulla Dhariwal
Alex Nichol
3.0K
10,306
0
11 May 2021
Learning Transferable Visual Models From Natural Language Supervision
International Conference on Machine Learning (ICML), 2021
Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya A. Ramesh
Gabriel Goh
...
Amanda Askell
Pamela Mishkin
Jack Clark
Gretchen Krueger
Ilya Sutskever
CLIP
VLM
2.0K
41,259
0
26 Feb 2021
Score-Based Generative Modeling through Stochastic Differential Equations
International Conference on Learning Representations (ICLR), 2020
Yang Song
Jascha Narain Sohl-Dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
Ben Poole
DiffM
SyDa
2.2K
8,890
0
26 Nov 2020
Denoising Diffusion Implicit Models
International Conference on Learning Representations (ICLR), 2020
Jiaming Song
Chenlin Meng
Stefano Ermon
VLM
DiffM
1.5K
10,230
0
06 Oct 2020
Learning to summarize from human feedback
Neural Information Processing Systems (NeurIPS), 2020
Nisan Stiennon
Long Ouyang
Jeff Wu
Daniel M. Ziegler
Ryan J. Lowe
Chelsea Voss
Alec Radford
Dario Amodei
Paul Christiano
ALM
865
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0
02 Sep 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
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19 Jun 2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Journal of machine learning research (JMLR), 2019
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
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23,849
0
23 Oct 2019
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
Sergey Levine
AI4CE
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400
764
0
02 May 2018
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
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8,853
0
12 Mar 2015
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