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2307.01850
Cited By
Self-Consuming Generative Models Go MAD
International Conference on Learning Representations (ICLR), 2023
4 July 2023
Sina Alemohammad
Josue Casco-Rodriguez
Lorenzo Luzi
Ahmed Imtiaz Humayun
Hossein Babaei
Daniel LeJeune
Ali Siahkoohi
Richard G. Baraniuk
WIGM
Re-assign community
ArXiv (abs)
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HuggingFace (1 upvotes)
Papers citing
"Self-Consuming Generative Models Go MAD"
50 / 122 papers shown
Aligning Instruction Tuning with Pre-training
Yiming Liang
Tianyu Zheng
Xinrun Du
Ge Zhang
Qingbin Liu
...
Guoyin Wang
Rundong Wang
Wenhao Huang
Jiajun Zhang
Xiang Yue
662
8
0
16 Jan 2025
Spatial Information Integration in Small Language Models for Document Layout Generation and Classification
ACM Symposium on Applied Computing (SAC), 2025
Pablo Melendez
Clemens Havas
223
0
0
09 Jan 2025
Malware Classification using a Hybrid Hidden Markov Model-Convolutional Neural Network
Ritik Mehta
Olha Jurecková
Mark Stamp
313
160
0
25 Dec 2024
Rate of Model Collapse in Recursive Training
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
A. Suresh
A. Thangaraj
Aditya Nanda Kishore Khandavally
SyDa
212
11
0
23 Dec 2024
Why Does ChatGPT "Delve" So Much? Exploring the Sources of Lexical Overrepresentation in Large Language Models
International Conference on Computational Linguistics (COLING), 2024
Tom S. Juzek
Zina B. Ward
322
8
0
16 Dec 2024
The Superalignment of Superhuman Intelligence with Large Language Models
Science China Information Sciences (Sci. China Inf. Sci.), 2024
Shiyu Huang
Yingkang Wang
Shiyao Cui
Pei Ke
J. Tang
451
1
0
15 Dec 2024
Image Generation Diversity Issues and How to Tame Them
Computer Vision and Pattern Recognition (CVPR), 2024
Mischa Dombrowski
Weitong Zhang
Sarah Cechnicka
Hadrien Reynaud
Bernhard Kainz
322
11
0
25 Nov 2024
Uncovering Hidden Subspaces in Video Diffusion Models Using Re-Identification
Mischa Dombrowski
Hadrien Reynaud
Bernhard Kainz
DiffM
253
2
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07 Nov 2024
DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios
Neural Information Processing Systems (NeurIPS), 2024
Junchao Wu
Runzhe Zhan
Yang Li
Shu Yang
Xinyi Yang
Yulin Yuan
Lidia S. Chao
DeLMO
619
19
0
31 Oct 2024
Universality of the
π
2
/
6
π^2/6
π
2
/6
Pathway in Avoiding Model Collapse
Apratim Dey
D. Donoho
306
15
0
30 Oct 2024
Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models
Wenda Li
Huijie Zhang
Qing Qu
WIGM
433
2
0
28 Oct 2024
Intention Is All You Need
Advait Sarkar
214
7
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24 Oct 2024
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
612
36
0
22 Oct 2024
Bias Amplification: Large Language Models as Increasingly Biased Media
Ze Wang
Zekun Wu
Jeremy Zhang
Navya Jain
Xin Guan
Skylar Lu
Saloni Gupta
Adriano Soares Koshiyama
356
0
0
19 Oct 2024
Data Diversity as Implicit Regularization: How Does Diversity Shape the Weight Space of Deep Neural Networks?
Yang Ba
M. Mancenido
Rong Pan
275
0
0
18 Oct 2024
Are AI Detectors Good Enough? A Survey on Quality of Datasets With Machine-Generated Texts
German Gritsai
Anastasia Voznyuk
Andrey Grabovoy
Yury Chekhovich
DeLMO
359
13
0
18 Oct 2024
Towards Reliable Verification of Unauthorized Data Usage in Personalized Text-to-Image Diffusion Models
IEEE Symposium on Security and Privacy (S&P), 2024
Boheng Li
Yanhao Wei
Yankai Fu
Ziyi Wang
Yiming Li
Jie Zhang
Run Wang
Minlie Huang
DiffM
AAML
207
20
0
14 Oct 2024
Will the Inclusion of Generated Data Amplify Bias Across Generations in Future Image Classification Models?
Zeliang Zhang
Xin Liang
Mingqian Feng
Susan Liang
Chenliang Xu
201
1
0
14 Oct 2024
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
International Conference on Learning Representations (ICLR), 2024
Aymane El Firdoussi
Abdalgader Abubaker
Soufiane Hayou
Réda Alami
Ahmed Alzubaidi
Hakim Hacid
348
5
0
11 Oct 2024
Strong Model Collapse
International Conference on Learning Representations (ICLR), 2024
Elvis Dohmatob
Yunzhen Feng
Arjun Subramonian
Julia Kempe
279
35
0
07 Oct 2024
Self-Improving Diffusion Models with Synthetic Data
Sina Alemohammad
Ahmed Imtiaz Humayun
S. Agarwal
John Collomosse
Richard G. Baraniuk
205
29
0
29 Aug 2024
Self-Directed Synthetic Dialogues and Revisions Technical Report
Nathan Lambert
Hailey Schoelkopf
Aaron Gokaslan
Luca Soldaini
Valentina Pyatkin
Louis Castricato
SyDa
174
5
0
25 Jul 2024
DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim
Jessica Bader
Stephan Alaniz
Cordelia Schmid
Zeynep Akata
237
23
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15 Jul 2024
Predicting vs. Acting: A Trade-off Between World Modeling & Agent Modeling
Margaret Li
Weijia Shi
Artidoro Pagnoni
Peter West
Ari Holtzman
232
16
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02 Jul 2024
A survey on the impacts of recommender systems on users, items, and human-AI ecosystems
Luca Pappalardo
Emanuele Ferragina
Salvatore Citraro
Giuliano Cornacchia
M. Nanni
...
Gabriele Barlacchi
Virginia Morini
Valentina Pansanella
D. Pedreschi
Emanuele Ferragina
262
16
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29 Jun 2024
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
Amrith Rajagopal Setlur
Saurabh Garg
Xinyang Geng
Naman Garg
Virginia Smith
Aviral Kumar
479
96
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20 Jun 2024
Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models
Jie Chen
Yupeng Zhang
Bingning Wang
Wayne Xin Zhao
Ji-Rong Wen
Weipeng Chen
SyDa
319
17
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18 Jun 2024
Understanding Hallucinations in Diffusion Models through Mode Interpolation
Sumukh K. Aithal
Pratyush Maini
Zachary Chase Lipton
J. Zico Kolter
DiffM
369
62
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13 Jun 2024
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Reinforcement
Yunzhen Feng
Elvis Dohmatob
Pu Yang
Francois Charton
Julia Kempe
245
17
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11 Jun 2024
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model Edits
Minzhou Pan
Yi Zeng
Xue Lin
Ning Yu
Cho-Jui Hsieh
Peter Henderson
Ruoxi Jia
WIGM
316
10
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06 Jun 2024
Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop
Yuqi Zhou
Sunhao Dai
Liang Pang
Gang Wang
Zhenhua Dong
Jun Xu
Jirong Wen
307
8
0
28 May 2024
Sociotechnical Implications of Generative Artificial Intelligence for Information Access
Bhaskar Mitra
Henriette Cramer
Olya Gurevich
297
10
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19 May 2024
Crowdsourcing with Enhanced Data Quality Assurance: An Efficient Approach to Mitigate Resource Scarcity Challenges in Training Large Language Models for Healthcare
Prosanta Barai
Gondy Leroy
Prakash Bisht
Joshua M Rothman
Sumi Lee
Jennifer G. Andrews
Sydney A Rice
Arif Ahmed
187
3
0
16 May 2024
At the edge of a generative cultural precipice
Diego Porres
Alex Gomez-Villa
144
0
0
30 Apr 2024
A Survey on Self-Evolution of Large Language Models
Zhengwei Tao
Ting-En Lin
Xiancai Chen
Hangyu Li
Yuchuan Wu
Yongbin Li
Zhi Jin
Fei Huang
Dacheng Tao
Jingren Zhou
LRM
LM&Ro
302
46
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22 Apr 2024
RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs
Shreyas Chaudhari
Pranjal Aggarwal
Vishvak Murahari
Tanmay Rajpurohit
Ashwin Kalyan
Karthik Narasimhan
Ameet Deshpande
Bruno Castro da Silva
407
88
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12 Apr 2024
Balanced Mixed-Type Tabular Data Synthesis with Diffusion Models
Zeyu Yang
Peikun Guo
Khadija Zanna
Akane Sano
Xiaoxue Yang
Akane Sano
DiffM
433
11
0
12 Apr 2024
G-NeRF: Geometry-enhanced Novel View Synthesis from Single-View Images
Zixiong Huang
Qi Chen
Libo Sun
Yifan Yang
Naizhou Wang
Zhuliang Yu
Qi Wu
3DV
170
5
0
11 Apr 2024
Heat Death of Generative Models in Closed-Loop Learning
IEEE Conference on Decision and Control (CDC), 2024
Matteo Marchi
Stefano Soatto
Pratik Chaudhari
Paulo Tabuada
SyDa
VLM
AI4CE
202
25
0
02 Apr 2024
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
Matthias Gerstgrasser
Rylan Schaeffer
Apratim Dey
Rafael Rafailov
Henry Sleight
...
Andrey Gromov
Daniel A. Roberts
Diyi Yang
D. Donoho
Oluwasanmi Koyejo
309
105
0
01 Apr 2024
Structured Evaluation of Synthetic Tabular Data
Scott Cheng-Hsin Yang
Baxter S. Eaves
Michael Schmidt
Ken Swanson
Patrick Shafto
298
7
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15 Mar 2024
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias
Conference on Fairness, Accountability and Transparency (FAccT), 2024
Sierra Wyllie
Ilia Shumailov
Nicolas Papernot
237
52
0
12 Mar 2024
Large Language Models for Data Annotation: A Survey
Zhen Tan
Dawei Li
Song Wang
Alimohammad Beigi
Bohan Jiang
Amrita Bhattacharjee
Mansooreh Karami
Wenlin Yao
Lu Cheng
Huan Liu
SyDa
397
87
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21 Feb 2024
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu
Sen Zhang
Yingjie Wang
Xinmei Tian
Dacheng Tao
291
21
0
19 Feb 2024
How to Train Data-Efficient LLMs
Noveen Sachdeva
Benjamin Coleman
Wang-Cheng Kang
Jianmo Ni
Lichan Hong
Ed H. Chi
James Caverlee
Julian McAuley
D. Cheng
267
90
0
15 Feb 2024
Model Collapse Demystified: The Case of Regression
Elvis Dohmatob
Yunzhen Feng
Julia Kempe
360
60
0
12 Feb 2024
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping
Haoyu Wang
Guozheng Ma
Ziqiao Meng
Zeyu Qin
Li Shen
...
Liu Liu
Yatao Bian
Qifeng Bai
Xueqian Wang
Peilin Zhao
271
18
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12 Feb 2024
Self-Correcting Self-Consuming Loops for Generative Model Training
International Conference on Machine Learning (ICML), 2024
Nate Gillman
Michael Freeman
Daksh Aggarwal
Chia-Hong Hsu
Calvin Luo
Yonglong Tian
Chen Sun
345
23
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11 Feb 2024
A Tale of Tails: Model Collapse as a Change of Scaling Laws
International Conference on Machine Learning (ICML), 2024
Elvis Dohmatob
Yunzhen Feng
Pu Yang
Francois Charton
Julia Kempe
320
107
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10 Feb 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
Tara Akhound-Sadegh
Jarrid Rector-Brooks
A. Bose
Sarthak Mittal
Pablo Lemos
...
Siamak Ravanbakhsh
Gauthier Gidel
Yoshua Bengio
Nikolay Malkin
Alexander Tong
DiffM
275
89
0
09 Feb 2024
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