A decoupled four-stage LLM pipeline with rsLoRA, distillation, and CoVe aggregation outperforms larger models on smart contract vulnerability detection and explanation using only 0.6B-4B parameter models.
Small language models for efficient agentic tool calling: Outperforming large models with targeted fine-tuning,
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Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation
A decoupled four-stage LLM pipeline with rsLoRA, distillation, and CoVe aggregation outperforms larger models on smart contract vulnerability detection and explanation using only 0.6B-4B parameter models.