Applied Domain Adaptation of LLM-based Document Embeddings for Engineering Knowledge Retrieval

Figure 1: Overview of our proposed domain adaptation pipeline designed for document embedding model fine-tuning for engineering knowledge retrieval.Our experiments include proper model selection (bottom), corpus curation and synthetic retrieval data generation (upper-left), and multiple fine-tuning configurations (upper-right).

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3759355.3759360
Primary Topic
biodegradable polymer synthesis and properties
Type
article
Field-Weighted Citation Impact
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article

Applied Domain Adaptation of LLM-based Document Embeddings for Engineering Knowledge Retrieval

biodegradable polymer synthesis and properties
article

Applied Domain Adaptation of LLM-based Document Embeddings for Engineering Knowledge Retrieval

article en

Abstract

Figure 1: Overview of our proposed domain adaptation pipeline designed for document embedding model fine-tuning for engineering knowledge retrieval.Our experiments include proper model selection (bottom), corpus curation and synthetic retrieval data generation (upper-left), and multiple fine-tuning configurations (upper-right).

Eötvös Loránd University (HU), Robert Bosch (Hungary)
Openalex Percentile: Top 56%
biodegradable polymer synthesis and properties
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Applied Domain Adaptation of LLM-based Document Embeddings for Engineering Knowledge Retrieval · (2025) | TGRS Research Map | TGRS