Core Concepts
Customizing LLMs with Search-Adaptor for improved information retrieval performance.
Abstract
Directory:
Abstract
Introduction
Large Language Models (LLMs) in Information Retrieval
Pre-Trained LLM Limitations and Search-Adaptor Proposal
Components of Search-Adaptor Methodology
Experimental Results and Performance Improvements
Ablation Studies on Search-Adaptor Variants
Key Highlights:
Proposal of Search-Adaptor method for customizing LLMs.
Importance of semantic embeddings in information retrieval.
Challenges with pre-trained LLMs and the need for tuning.
Description of components like adaptation function, ranking loss, and regularizers in Search-Adaptor.
Significant performance improvements across various datasets using Search-Adaptor.
Stats
Search-Adaptorは、Google埋め込みAPIのnDCG@10で14 BEIRデータセットで5%以上の改善を示しました。