Data Feedback Loops: Model-driven Amplification of Dataset Biases

Data Feedback Loops: Model-driven Amplification of Dataset Biases

8 September 2022

Tatsunori B. Hashimoto

Papers citing "Data Feedback Loops: Model-driven Amplification of Dataset Biases"

17 / 17 papers shown

Title
Position: Model Collapse Does Not Mean What You Think Rylan Schaeffer Joshua Kazdan Alvan Caleb Arulandu Sanmi Koyejo 62 0 0 05 Mar 2025
Economics of Sourcing Human Data Sebastin Santy Prasanta Bhattacharya Manoel Horta Ribeiro Kelsey Allen Sewoong Oh 74 0 0 11 Feb 2025
FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Yining She Sumon Biswas Christian Kastner Eunsuk Kang 42 0 0 03 Jan 2025
Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streams Brandon Gower-Winter Georg Krempl Sergey Dragomiretskiy Tineke Jelsma Arno Siebes 88 0 0 13 Dec 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 50 11 0 22 Oct 2024
Addressing Discretization-Induced Bias in Demographic Prediction Evan Dong Aaron Schein Yixin Wang Nikhil Garg 37 3 0 27 May 2024
A Mathematical Model of the Hidden Feedback Loop Effect in Machine Learning Systems Andrey Veprikov Alexander Afanasiev Anton Khritankov 40 2 0 04 May 2024
Predictive Minds: LLMs As Atypical Active Inference Agents Jan Kulveit Clem von Stengel Roman Leventov LLMAG KELM LRM 44 1 0 16 Nov 2023
Discovering and Mitigating Visual Biases through Keyword Explanation Younghyun Kim Sangwoo Mo Minkyu Kim Kyungmin Lee Jaeho Lee Jinwoo Shin 40 32 0 26 Jan 2023
A Systematic Study of Bias Amplification Melissa Hall L. V. D. van der Maaten Laura Gustafson Maxwell Jones Aaron B. Adcock 102 70 0 27 Jan 2022
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 150 39 0 12 Oct 2021
Outside the Echo Chamber: Optimizing the Performative Risk John Miller Juan C. Perdomo Tijana Zrnic 76 97 0 17 Feb 2021
How to Learn when Data Reacts to Your Model: Performative Gradient Descent Zachary Izzo Lexing Ying James Zou 84 74 0 15 Feb 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 253 1,989 0 31 Dec 2020
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,815 0 14 Dec 2020
The Woman Worked as a Babysitter: On Biases in Language Generation Emily Sheng Kai-Wei Chang Premkumar Natarajan Nanyun Peng 214 616 0 03 Sep 2019
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility A. Chaney Brandon M Stewart Barbara E. Engelhardt CML 169 313 0 30 Oct 2017