Segment-Level Agentic Topic Modeling for Improved Data Exploration and Resource Efficiency

Paper recorded by Signals 4 on 2026-09-25 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28

Category: cs.AI · 人工智能 · first seen 2026-09-28

Abstract

Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a variety of industry sectors. Recently, large language model (LLM)-based topic models have been emerged that prompt LLMs to generate topics then assign the topics to documents, producing more natural and human-readable topics than conventional topic mo

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