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Main Authors: Sumyk, Marta, Kosovan, Oleksandr
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.14896
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author Sumyk, Marta
Kosovan, Oleksandr
author_facet Sumyk, Marta
Kosovan, Oleksandr
contents We present an initial investigation into Agentic Retrieval-Augmented Generation (RAG) for Ukrainian, conducted within the UNLP 2026 Shared Task on Multi-Domain Document Understanding. Our system combines two-stage retrieval (BGE-M3 with BGE reranking) with a lightweight agentic layer performing query rephrasing and answer-retry loops on top of Qwen2.5-3B-Instruct. Our analysis reveals that retrieval quality is the primary bottleneck: agentic retry mechanisms improve answer accuracy but the overall score remains constrained by document and page identification. We discuss practical limitations of offline agentic pipelines and outline directions for combining stronger retrieval with more advanced agentic reasoning for Ukrainian.
format Preprint
id arxiv_https___arxiv_org_abs_2604_14896
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Toward Agentic RAG for Ukrainian
Sumyk, Marta
Kosovan, Oleksandr
Artificial Intelligence
We present an initial investigation into Agentic Retrieval-Augmented Generation (RAG) for Ukrainian, conducted within the UNLP 2026 Shared Task on Multi-Domain Document Understanding. Our system combines two-stage retrieval (BGE-M3 with BGE reranking) with a lightweight agentic layer performing query rephrasing and answer-retry loops on top of Qwen2.5-3B-Instruct. Our analysis reveals that retrieval quality is the primary bottleneck: agentic retry mechanisms improve answer accuracy but the overall score remains constrained by document and page identification. We discuss practical limitations of offline agentic pipelines and outline directions for combining stronger retrieval with more advanced agentic reasoning for Ukrainian.
title Toward Agentic RAG for Ukrainian
topic Artificial Intelligence
url https://arxiv.org/abs/2604.14896