Model Editing

45 papers with code • 0 benchmarks • 1 datasets

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Use these libraries to find Model Editing models and implementations
3 papers


Most implemented papers

Fast Model Editing at Scale

eric-mitchell/mend ICLR 2022

To enable easy post-hoc editing at scale, we propose Model Editor Networks using Gradient Decomposition (MEND), a collection of small auxiliary editing networks that use a single desired input-output pair to make fast, local edits to a pre-trained model's behavior.

Editing Large Language Models: Problems, Methods, and Opportunities

zjunlp/easyedit 22 May 2023

Our objective is to provide valuable insights into the effectiveness and feasibility of each editing technique, thereby assisting the community in making informed decisions on the selection of the most appropriate method for a specific task or context.

pyvene: A Library for Understanding and Improving PyTorch Models via Interventions

stanfordnlp/pyvene 12 Mar 2024

Interventions on model-internal states are fundamental operations in many areas of AI, including model editing, steering, robustness, and interpretability.

Locating and Editing Factual Associations in GPT

kmeng01/rome 10 Feb 2022

To test our hypothesis that these computations correspond to factual association recall, we modify feed-forward weights to update specific factual associations using Rank-One Model Editing (ROME).

Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values

interpretml/interpret 30 Jun 2022

Machine learning (ML) interpretability techniques can reveal undesirable patterns in data that models exploit to make predictions--potentially causing harms once deployed.

A Comprehensive Study of Knowledge Editing for Large Language Models

zjunlp/easyedit 2 Jan 2024

In this paper, we first define the knowledge editing problem and then provide a comprehensive review of cutting-edge approaches.

ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale

cap-ntu/ML-Model-CI 18 May 2021

AI engineering has emerged as a crucial discipline to democratize deep neural network (DNN) models among software developers with a diverse background.

Learning to Model Editing Processes

machelreid/editpro 24 May 2022

We introduce baseline results and metrics on this task, finding that modeling editing processes improves performance on a variety of axes on both our proposed task and related downstream tasks compared to previous single-step models of edits.

Language Anisotropic Cross-Lingual Model Editing

franklear/lime 25 May 2022

On the newly defined cross-lingual model editing task, we empirically demonstrate the failure of monolingual baselines in propagating the edit to multiple languages and the effectiveness of the proposed language anisotropic model editing.

Memory-Based Model Editing at Scale

eric-mitchell/serac 13 Jun 2022

We find that only SERAC achieves high performance on all three problems, consistently outperforming existing approaches to model editing by a significant margin.