Must-read Papers on Knowledge Editing for Large Language Models.
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Updated
Sep 28, 2024
Must-read Papers on Knowledge Editing for Large Language Models.
[ACL 2024] An Easy-to-use Hallucination Detection Framework for LLMs.
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System.
[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers
Code and dataset for the paper: "Can Editing LLMs Inject Harm?"
[EMNLP 2024 Findings] To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models
Code for "Learning to Edit: Aligning LLMs with Knowledge Editing (ACL 2024)"
Official implementation for Zhong & Le et al., GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024
Debiasing Stereotyped Language Models via Model Editing
An Automated Framework to Construct Datasets for Assessing Knowledge Editing or Multi-Hop Reasoning Capability of Language Models.
[ICLR 2024] Unveiling the Pitfalls of Knowledge Editing for Large Language Models
MLaKE: Multilingual Knowledge Editing Benchmark for Large Language Models
Official codes for COLING 2024 paper "Robust and Scalable Model Editing for Large Language Models": https://arxiv.org/abs/2403.17431v1
Stable Knowledge Editing in Large Language Models
EMNLP'23 survey: a curation of awesome papers and resources on refreshing large language models (LLMs) without expensive retraining.
Official code repo for "Editing Implicit Assumptions in Text-to-Image Diffusion Models"
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