Humanities‐in‐the‐Loop: Using Close Reading as a Method for Retrieval‐Augmented Generation ( <scp>RAG</scp> )

ABSTRACT This paper proposes Humanities‐in‐the‐Loop, a methodological framework that embeds close reading into each stage of the Retrieval‐Augmented Generation (RAG) pipeline to enhance the processing of digital archival materials. This framework includes manual annotation, knowledge maintenance, reviewer validation, prompt engineering, and human interpretation. Taking the diaries of Coching Chu as a case study, the system addresses the limitations of conventional RAG methods in capturing the contextual complexity and historical nuance inherent in personal archives. An evaluation further confirms the effectiveness of this approach in delivering faithful, contextually grounded responses. The proposed framework not only enhances answer accuracy and interpretability but also enables traceable, human‐centered inquiry in digital humanities research.

Institutions

Publication Details

Journal
Proceedings of the Association for Information Science and Technology
Published
2025-10-01
DOI
https://doi.org/10.1002/pra2.1355
Primary Topic
Digital Humanities and Scholarship
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Humanities‐in‐the‐Loop: Using Close Reading as a Method for Retrieval‐Augmented Generation ( RAG )

Proceedings of the Association for Information Science and Technology
Digital Humanities and Scholarship
article

Humanities‐in‐the‐Loop: Using Close Reading as a Method for Retrieval‐Augmented Generation ( RAG )

article en

Abstract

ABSTRACT This paper proposes Humanities‐in‐the‐Loop, a methodological framework that embeds close reading into each stage of the Retrieval‐Augmented Generation (RAG) pipeline to enhance the processing of digital archival materials. This framework includes manual annotation, knowledge maintenance, reviewer validation, prompt engineering, and human interpretation. Taking the diaries of Coching Chu as a case study, the system addresses the limitations of conventional RAG methods in capturing the contextual complexity and historical nuance inherent in personal archives. An evaluation further confirms the effectiveness of this approach in delivering faithful, contextually grounded responses. The proposed framework not only enhances answer accuracy and interpretability but also enables traceable, human‐centered inquiry in digital humanities research.

Proceedings of the Association for Information Science and TechnologyVol. 62(1)
Wuhan University (CN)
Quality Education
Openalex Percentile: Top 41%
Digital Humanities and Scholarship
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.