LETHE uses parameter-level model merging plus prompt-level word definitions to dilute backdoor behavior in LLMs, cutting attack success to below 7% in most tested settings.
Model soups: Averaging weights of multiple fine-tuned models improves accuracy with- out increasing inference time
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Lethe: Purifying Backdoored Large Language Models with Knowledge Dilution
LETHE uses parameter-level model merging plus prompt-level word definitions to dilute backdoor behavior in LLMs, cutting attack success to below 7% in most tested settings.