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Direct Preference Optimization (DPO) has been proposed as an effective and efficient alternative to reinforcement learning from human feedback (RLHF).
Reverse-time diffusion equation models
Brian D.O. Anderson · 1982
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BLEU: A Method for Automatic Evaluation of Machine Translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Reinforcement learning by reward-weighted regression for operational space control
Jan Peters and Stefan Schaal · 2007
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Curriculum Learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Self-paced learning for latent variable models
M. Kumar, Benjamin Packer, and Daphne Koller · 2010
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Self-paced curriculum learning
Lu Jiang, Deyu Meng, Qian Zhao, Shiguang Shan, and Alexander Hauptmann · 2015
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Deep unsupervised learning using non-equilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Deep Reinforcement Learning from Human Preferences
Paul F. Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Curriculum dropout
Pietro Morerio, Jacopo Cavazza, Riccardo Volpi, René Vidal, and Vittorio Murino · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Curriculum Learning for Natural Answer Generation
Cao Liu, Shizhu He, Kang Liu, and Jun Zhao · 2018
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On-line adaptative curriculum learning for GANs
Thang Doan, Joao Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, and R. Devon Hjelm · 2019
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Balanced self-paced learning for generative adversarial clustering network
Kamran Ghasedi, Xiaoqian Wang, Cheng Deng, and Heng Huang · 2019
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Medical-based Deep Curriculum Learning for Improved Fracture Classification
Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Miguel A. González Ballester, and Gemma Piella · 2019
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Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng, Aviral Kumar, Grace Zhang, and Sergey Levine · 2019
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Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Nils Reimers and Iryna Gurevych · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Energy and Policy Considerations for Deep Learning in NLP
Emma Strubell, Ananya Ganesh, and Andrew Mccallum · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Analyzing and improving the image quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Green AI
Roy Schwartz, Jesse Dodge, Noah A. Smith, and Oren Etzioni · 2020
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Curriculum by Smoothing
Samarth Sinha, Animesh Garg, and Hugo Larochelle · 2020
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Image difficulty curriculum for generative adversarial networks (CuGAN)
Petru Soviany, Claudiu Ardei, Radu Tudor Ionescu, and Marius Leordeanu · 2020
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Fine-Tuning Language Models from Human Preferences
Daniel M. Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B. Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving · 2020
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Score-based generative neural networks for large-scale optimal transport
Max Daniels, Tyler Maunu, and Paul Hand · 2021
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2021
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Variational diffusion models
Diederik Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
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SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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LAION-Aesthetics
Christoph Schuhmann · 2022
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Curriculum learning: A survey
Petru Soviany, Radu Tudor Ionescu, Paolo Rota, and Nicu Sebe · 2022
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AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise
Julian Wyatt, Adam Leach, Sebastian M. Schmon, and Chris G. Willcocks · 2022
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Diffusion models in vision: A survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah · 2023
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Curriculum self-paced learning for cross-domain object detection
Petru Soviany, Radu Tudor Ionescu, Paolo Rota, and Nicu Sebe · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry Wei, Arief Suriawinata, Bing Ren, Xiaoying Liu, Mikhail Lisovsky, Louis Vaickus, Charles Brown, Michael Baker, Mustafa Nasir-Moin, Naofumi Tomita, Lorenzo Torresani, Jason Wei, and Saeed Hassanpour · 2021
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Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
Cited alongside, same era.
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DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee · 2023
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Pick-a-pic: An open dataset of user preferences for text-to-image generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2023
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Aligning text-to-image models using human feedback
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, and Shixiang Shane Gu · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, and Chelsea Finn · 2023
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Consistency models
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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EfficientTrain: Exploring Generalized Curriculum Learning for Training Visual Backbones
Yulin Wang, Yang Yue, Rui Lu, Tianjiao Liu, Zhao Zhong, Shiji Song, and Gao Huang · 2023
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Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, and Hongsheng Li · 2023
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Adding Conditional Control to Text-to-Image Diffusion Models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Phi-3 technical report: A highly capable language model locally on your phone
Marah Abdin, Jyoti Aneja, Hany Awadalla, Ahmed Awadallah, Ammar Ahmad Awan, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Jianmin Bao, Harkirat Behl, et al · 2024
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Training Diffusion Models with Reinforcement Learning
Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, and Sergey Levine · 2024
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Teaching large language models to reason with reinforcement learning
Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, Christoforos Nalmpantis, Jane Dwivedi-Yu, Maksym Zhuravinskyi, Eric Hambro, Sainbayar Sukhbaatar, and Roberta Raileanu · 2024
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CL-MAE: Curriculum-Learned Masked Autoencoders
Neelu Madan, Nicolae-Cătălin Ristea, Kamal Nasrollahi, Thomas B. Moeslund, and Radu Tudor Ionescu · 2024
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Improved Techniques for Training Consistency Models
Yang Song and Prafulla Dhariwal · 2024
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Diffusion Model Alignment Using Direct Preference Optimization
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, and Nikhil Naik · 2024
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Towards Faster Training of Diffusion Models: An Inspiration of A Consistency Phenomenon
Tianshuo Xu, Peng Mi, Ruilin Wang, and Yingcong Chen · 2024
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Denoising task difficulty-based curriculum for training diffusion models
Jin-Young Kim, Hyojun Go, Soonwoo Kwon, and Hyun-Gyoon Kim · 2025
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