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Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approach for knowledge injection during large language model (LLM) inference in recent years. However, due to their limited ability to exploit fine-grained inter-document…

Computation and Language · Computer Science 2025-09-09 Weitao Li , Kaiming Liu , Xiangyu Zhang , Xuanyu Lei , Weizhi Ma , Yang Liu

Extensible Markup Language (XML) is a widely used file format for data storage and transmission. Many XML processors support XPath, a query language that enables the extraction of elements from XML documents. These systems can be affected…

Software Engineering · Computer Science 2024-01-11 Shuxin Li , Manuel Rigger

Retrieval-Augmented Generation (RAG) based on Large Language Models (LLMs) is a powerful solution to understand and query the industry's closed-source documents. However, basic RAG often struggles with complex QA tasks in legal and…

Information Retrieval · Computer Science 2025-09-08 Huifeng Lin , Gang Su , Jintao Liang , You Wu , Rui Zhao , Ziyue Li

Data represented as strings abounds in biology, linguistics, document mining, web search and many other fields. Such data often have a hierarchical structure, either because they were artificially designed and composed in a hierarchical…

Artificial Intelligence · Computer Science 2016-06-14 Payam Siyari , Bistra Dilkina , Constantine Dovrolis

We present a new benchmark for evaluating Deep Search--a realistic and complex form of retrieval-augmented generation (RAG) that requires source-aware, multi-hop reasoning over diverse, sparsed, but related sources. These include documents,…

Computation and Language · Computer Science 2025-07-01 Prafulla Kumar Choubey , Xiangyu Peng , Shilpa Bhagavath , Kung-Hsiang Huang , Caiming Xiong , Chien-Sheng Wu

As an effective method to boost the performance of Large Language Models (LLMs) on the question answering (QA) task, Retrieval-Augmented Generation (RAG), which queries highly relevant information from external complex documents, has…

Information Retrieval · Computer Science 2025-12-04 Shu Wang , Yingli Zhou , Yixiang Fang

Large Language Model (LLM)-based search agents have shown remarkable capabilities in solving complex tasks by dynamically decomposing problems and addressing them through interleaved reasoning and retrieval. However, this interleaved…

Artificial Intelligence · Computer Science 2025-05-20 Tiannuo Yang , Zebin Yao , Bowen Jin , Lixiao Cui , Yusen Li , Gang Wang , Xiaoguang Liu

Retrieval-Augmented Generation (RAG) systems commonly use chunking strategies for retrieval, which enhance large language models (LLMs) by enabling them to access external knowledge, ensuring that the retrieved information is up-to-date and…

Computation and Language · Computer Science 2025-07-15 Hai Toan Nguyen , Tien Dat Nguyen , Viet Ha Nguyen

This paper addresses the challenge of improving information retrieval from semi-structured eXtensible Markup Language (XML) documents. Traditional information retrieval systems (IRS) often overlook user-specific needs and return identical…

Information Retrieval · Computer Science 2026-03-24 Ounnaci Iddir , Ahmed-ouamer Rachid , Tai Dinh

Retrieval-Augmented Generation (RAG) is widely used to ground large language models in external knowledge sources. However, when applied to heterogeneous corpora and multi-step queries, Naive RAG pipelines often degrade in quality due to…

Information Retrieval · Computer Science 2026-04-10 Valeriy Kovalskiy , Nikita Belov , Nikita Miteyko , Igor Reshetnikov , Max Maximov

In this paper, proximity full-text searches in large text arrays are considered. A search query consists of several words. The search result is a list of documents containing these words. In a modern search system, documents that contain…

Information Retrieval · Computer Science 2020-06-28 Alexander B. Veretennikov

Locating and distilling the valuable relevant information continued to be the major challenges of Information Retrieval (IR) Systems owing to the explosive growth of online web information. These challenges can be considered the XML…

Information Retrieval · Computer Science 2014-10-29 Suma D. , U. Dinesh Acharya , Geetha M. , Raviraja Holla M

Recently, keyword search on Knowledge Graphs (KGs) becomes popular. Typical keyword search approaches aim at finding a concise subgraph from a KG, which can reflect a close relationship among all input keywords. The connection paths between…

Databases · Computer Science 2020-01-22 Yueji Yang , Anthony K. H. Tung

This paper reports on the INRIA group's approach to XML mining while participating in the INEX XML Mining track 2005. We use a flexible representation of XML documents that allows taking into account the structure only or both the structure…

Information Retrieval · Computer Science 2007-05-23 Anne-Marie Vercoustre , Mounir Fegas , Saba Gul , Yves Lechevallier

With XML becoming an ubiquitous language for data interoperability purposes in various domains, efficiently querying XML data is a critical issue. This has lead to the design of algebraic frameworks based on tree-shaped patterns akin to the…

Databases · Computer Science 2017-01-18 Marouane Hachicha , Jérôme Darmont

At CCS 2015 Naveed et al. presented first attacks on efficiently searchable encryption, such as deterministic and order-preserving encryption. These plaintext guessing attacks have been further improved in subsequent work, e.g. by Grubbs et…

Cryptography and Security · Computer Science 2017-09-28 Florian Kerschbaum , Anselme Tueno

Due to the increasing storage data on Web Applications, it becomes very difficult to use only keyword-based searches to provide comprehensive search results, thus increasing the difficulty for web users to search information on the web. In…

Information Retrieval · Computer Science 2021-10-12 Ikechukwu Onyenwe , Stanley Ogbonna , Ebele Onyedimma , Onyedikachukwu Ikechukwu-Onyenwe , Chidinma Nwafor

Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML. Originally designed to meet the challenges of large-scale electronic publishing, XML is also playing an increasingly important role in the exchange…

Programming Languages · Computer Science 2007-10-26 J. M. Almendros-Jiménez , A. Becerra-Terón , F. J. Enciso-Baños

In enterprise settings, efficiently retrieving relevant information from large and complex knowledge bases is essential for operational productivity and informed decision-making. This research presents a systematic empirical framework for…

We present an algorithm for searching regular expression matches in compressed text. The algorithm reports the number of matching lines in the uncompressed text in time linear in the size of its compressed version. We define efficient data…

Formal Languages and Automata Theory · Computer Science 2019-01-17 Pierre Ganty , Pedro Valero