Will Large-scale Generative Models Corrupt Future Datasets?

15 November 2022

Papers citing "Will Large-scale Generative Models Corrupt Future Datasets?"

10 / 10 papers shown

Title
Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data? Grgur Kovač Jérémy Perez Rémy Portelas Peter Ford Dominey Pierre-Yves Oudeyer 33 0 0 04 Apr 2025
The Best Instruction-Tuning Data are Those That Fit Dylan Zhang Qirun Dai Hao Peng ALM 115 3 0 06 Feb 2025
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Nayoung Lee Ziyang Cai Avi Schwarzschild Kangwook Lee Dimitris Papailiopoulos ReLM VLM LRM AI4CE 73 4 0 03 Feb 2025
Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World Joshua Kazdan Rylan Schaeffer Apratim Dey Matthias Gerstgrasser Rafael Rafailov D. Donoho Sanmi Koyejo 45 11 0 22 Oct 2024
Nepotistically Trained Generative-AI Models Collapse Matyáš Boháček Hany Farid 46 17 0 20 Nov 2023
LAVIS: A Library for Language-Vision Intelligence Dongxu Li Junnan Li Hung Le Guangsen Wang Silvio Savarese S. Hoi VLM 113 51 0 15 Sep 2022
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 390 4,124 0 28 Jan 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 260 7,434 0 11 Nov 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,344 0 12 Dec 2018
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,190 0 01 Sep 2014