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Jul, 2024
TRACE:LLM中使用对比嵌入的基于Transformer的归因
TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs
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Cheng Wang, Xinyang Lu, See-Kiong Ng, Bryan Kian Hsiang Low
TL;DR
作者提出了一种新颖而多用途的基于TRansformer的自带对比嵌入的源归因框架TRACE,该框架利用对比学习实现源归因,通过广泛的实证评估证明TRACE在不同场景下的性能和效率,显著改善了源归因的准确性,从而增加了大语言模型的可靠性和可信度。
Abstract
The rapid evolution of
large language models
(LLMs) represents a substantial leap forward in natural language understanding and generation. However, alongside these advancements come significant challenges related to the
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