Repairing Neural Networks by Leaving the Right Past Behind

Repairing Neural Networks by Leaving the Right Past Behind

11 July 2022

Melanie F. Pradier

Papers citing "Repairing Neural Networks by Leaving the Right Past Behind"

9 / 9 papers shown

Title
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images Sheng-Yu Wang Aaron Hertzmann Alexei A. Efros Jun-Yan Zhu Richard Zhang TDI 123 2 0 21 Feb 2025
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models Yan Scholten Stephan Günnemann Leo Schwinn MU 55 6 0 04 Oct 2024
In-Context Editing: Learning Knowledge from Self-Induced Distributions Siyuan Qi Bangcheng Yang Kailin Jiang Xiaobo Wang Jiaqi Li Yifan Zhong Yaodong Yang Zilong Zheng KELM 99 8 0 17 Jun 2024
MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editing Jiaqi Li Miaozeng Du Chuanyi Zhang Yongrui Chen Nan Hu Guilin Qi Haiyun Jiang Siyuan Cheng Bo Tian 18 14 0 18 Feb 2024
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks Piyush Tiwary Atri Guha Subhodip Panda Prathosh A.P. MU GAN 53 7 0 25 Sep 2023
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 175 89 0 02 Dec 2021
Fast Model Editing at Scale E. Mitchell Charles Lin Antoine Bosselut Chelsea Finn Christopher D. Manning KELM 219 341 0 21 Oct 2021
A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging Thomas Henn Yasukazu Sakamoto Clément Jacquet Shunsuke Yoshizawa M. Andou ... R. Saga Hiroyuki Ishihara Katsuhiko Shimizu Yingzhen Li Ryutaro Tanno 108 9 0 25 Sep 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,659 0 09 Mar 2017