knowledge editing
32 papers with code • 1 benchmarks • 2 datasets
Libraries
Use these libraries to find knowledge editing models and implementations
KnowEdit
WikiFactDiff
Most implemented papers
Neighboring Perturbations of Knowledge Editing on Large Language Models
mjy1111/peak
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A metric of additivity is introduced and a benchmark dubbed as Perturbation Evaluation of Appending Knowledge (PEAK) is constructed to evaluate the degree of perturbation to neighboring knowledge when appending new knowledge.
Knowledge Editing on Black-box Large Language Models
Knowledge editing (KE) aims to efficiently and precisely modify the behavior of large language models (LLMs) to update specific knowledge without negatively influencing other knowledge.
Empirical Study on Updating Key-Value Memories in Transformer Feed-forward Layers
qiuzh20/tuning-keys-v.s.-values
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The feed-forward networks (FFNs) in transformers are recognized as a group of key-value neural memories to restore abstract high-level knowledge.
Learning to Edit: Aligning LLMs with Knowledge Editing
yjiangcm/lte
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Knowledge editing techniques, aiming to efficiently modify a minor proportion of knowledge in large language models (LLMs) without negatively impacting performance across other inputs, have garnered widespread attention.
Event-level Knowledge Editing
thu-keg/event-level-knowledge-editing
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However, natural knowledge updates in the real world come from the occurrences of new events rather than direct changes in factual triplets.
Stable Knowledge Editing in Large Language Models
The premise of localization results in an incomplete knowledge editing, whereas an isolated assumption may impair both other knowledge and general abilities.
InstructEdit: Instruction-based Knowledge Editing for Large Language Models
zjunlp/easyedit
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Knowledge editing for large language models can offer an efficient solution to alter a model's behavior without negatively impacting the overall performance.
Editing Conceptual Knowledge for Large Language Models
zjunlp/easyedit
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Recently, there has been a growing interest in knowledge editing for Large Language Models (LLMs).
BadEdit: Backdooring large language models by model editing
Lyz1213/BadEdit
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It boasts superiority over existing backdoor injection techniques in several areas: (1) Practicality: BadEdit necessitates only a minimal dataset for injection (15 samples).
Detoxifying Large Language Models via Knowledge Editing
zjunlp/easyedit
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This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs).
