Latest Retrieval-Augmented Generation Research Papers
The newest Retrieval-Augmented Generation papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Retrieval-Augmented Generation so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.
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- WAIT-A-SEC: A Human-Centered Design Approach to Privacy Communication for Social Media OversharingTimoteo Kelly, Praveen Rao · Zenodo (CERN European Organ... · Oct 23, 2026
Social media platforms often operate on extractive security logics that prioritize frictionless data sharing, leaving users disempowered and prone to oversharing sensitive information, without fully recognizing the associated privacy implic…
- WAIT-A-SEC: A Human-Centered Design Approach to Privacy Communication for Social Media OversharingTimoteo Kelly, Praveen Rao · Zenodo (CERN European Organ... · Oct 23, 2026
Social media platforms often operate on extractive security logics that prioritize frictionless data sharing, leaving users disempowered and prone to oversharing sensitive information, without fully recognizing the associated privacy implic…
- Universal Intelligent Document Management System Using OCR, Retrieval-Augmented Generation, and Large Language ModelsDr. K R Shylaja, Praveen H · Journal of Zhejiang Univers... · Sep 15, 2026
Abstract The rapid growth of digital information has significantly increased the need for intelligent systems capable of managing, understanding, and retrieving knowledge from diverse document formats. Traditional document management system…
- Universal Intelligent Document Management System Using OCR, Retrieval-Augmented Generation, and Large Language ModelsDr. K R Shylaja, Praveen H · Journal of Zhejiang Univers... · Sep 15, 2026
Abstract The rapid growth of digital information has significantly increased the need for intelligent systems capable of managing, understanding, and retrieving knowledge from diverse document formats. Traditional document management system…
- Domain-Specific Hallucination Detection in Large Language ModelsVarun Teja Chundru, Debasmita Biswas · arXiv · Sep 10, 2026
Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo (MC) Dropout unce…
- Whisper-Based Speech Transcription from Videos Across Multiple Languages for Cross-Cultural UnderstandingMichael Picheny · arXiv · Sep 10, 2026
Cross-cultural understanding has become increasingly important in today's highly connected, cross-national world. The success of LLM-based technologies is now driving the development of automated tools to aid understanding for nonnative peo…
- RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM SafetyAdithiyan Rajan Indira Saravanan, Kathleen C. Fraser · arXiv · Sep 10, 2026
Allowing large language models (LLMs) to retrieve information from a set of trusted documents can increase reliability and reduce hallucination. However, recent work has demonstrated that retrieval-augmented generation (RAG) can have uninte…
- SIRF: A Spec-Internalized Risk Foundation Model for Industrial Content Risk ControlSuwan Wu, Yumeng Lin, Pengcheng Yuan, Xiaolong Jiang · arXiv · Sep 10, 2026
For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision and second-level latency. We present SIRF (Spec-Internalized Risk Foundation Model), whic…
- Negative Self-Distillation: Learning to Reason by Avoiding FlawsRongcan Pei, Zhepei Wei, Shuyao Xu, Xinyu Zhu et al. · arXiv · Sep 10, 2026
On-Policy Self-Distillation (OPSD) has emerged as a popular paradigm for large language model (LLM) self-improvement, allowing models to act as their own teachers by leveraging privileged information such as ground-truth solutions. However,…
- Complex-Text Robustness Evaluation and Failure Diagnosis for Low-Resource Multilingual Text-to-SpeechTianlun Zuo, Ziyu Zhang, Tingzhi Mao, Zhonghua Fu et al. · arXiv · Sep 10, 2026
Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insufficiently diagnosed. Existing evaluations mainly focus on naturalness, speaker similarity, a…
- VikingRAG: Accurate and Token-efficient Retrieval-augmented Generation over Structured DocumentsPeiyuan Gao, Gaoyuan Zhang, Haojie Qin, Yahui Sun et al. · arXiv · Sep 10, 2026
State-of-the-art retrieval-augmented generation (RAG) methods exploit document structures to acquire sufficient evidence, but often incur substantial token costs. To reduce structural-context tokens without compromising high RAG accuracy, w…
- The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech DecodingGilad D. Landau, Dulhan Jayalath, Oiwi Parker Jones · arXiv · Sep 9, 2026
Non-invasive speech decoding remains constrained by the low signal-to-noise ratio of neural recordings, which makes fine-grained reconstruction of phonemes or individual words difficult. Motivated by neuroscientific evidence that high-level…
- KVShareArena: KV-Cache Reuse Across Contexts and Model CheckpointsXi Shi, Qian Lou · arXiv · Sep 9, 2026
LLM serving systems already reuse KV caches, but only when the reused text sits at the very start of the prompt. Two growing workloads break this condition: a retrieval-augmented generation server assembles a different set of retrieved chun…
- Evidence-Grounded Multi-Agent RAG for Automated Regulatory Compliance and Policy Auditing on Google Cloud: A Human-Governed Reference Architecture for GxP, FDA 21 CFR Part 11, HIPAA, and ICH E6(R3)Sarika Singh · Zenodo (CERN European Organ... · Sep 9, 2026
Regulated life-sciences and healthcare organizations increasingly need to evaluate large volumes of electronic records, standard operating procedures, clinical-trial artifacts, and policy evidence while preserving traceability, temporal val…
- Evidence-Grounded Multi-Agent RAG for Automated Regulatory Compliance and Policy Auditing on Google Cloud: A Human-Governed Reference Architecture for GxP, FDA 21 CFR Part 11, HIPAA, and ICH E6(R3)Sarika Singh · Zenodo (CERN European Organ... · Sep 9, 2026
Regulated life-sciences and healthcare organizations increasingly need to evaluate large volumes of electronic records, standard operating procedures, clinical-trial artifacts, and policy evidence while preserving traceability, temporal val…
- GuidelineGuard: An Agentic Retrieval-Augmented Generation Framework with Sentence-Level Citation Auditing for Guideline-Grounded Question AnsweringFarida Far Poor · Computation · Sep 9, 2026
Background: Large language models (LLMs) can produce clinically plausible recommendations that are not adequately supported by authoritative evidence. Objectives: We introduce GuidelineGuard, a modular multi-agent retrieval-augmented genera…
- Enterprise AI Architecture Governance and Risk FrameworkSanjeeve Kumar Gajadi · International Journal For M... · Sep 9, 2026
Artificial Intelligence (AI) is transforming modern enterprises by enabling intelligent automation, predictive analytics, generative AI, autonomous decision-making, digital assistants, and real-time optimization across business processes. A…
- STALL + : Boosting LLM-based Repository-level Code Completion with Static AnalysisLiu Jun-wei, Yixuan Chen, Mingwei Liu, Xin Peng et al. · ACM Transactions on Softwar... · Sep 9, 2026
Repository-level code completion refers to the challenging completion scenario involving complicated contexts from multiple files in a repository. To date, researchers have proposed two technical categories to enhance LLM-based repository-l…
- Advances in Reinforcement Learning for Retrieval-Augmented Generation in Large Language ModelZunlong Hong · Applied and Computational E... · Sep 8, 2026
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external information, but traditional fixed retrieval processes struggle to adapt to complex task requirements. In recent years, reinforcement learn…
- Application of Knowledge Graph-Based GraphRAG in Intelligent Question Answering SystemsFanhao Zhou · Applied and Computational E... · Sep 8, 2026
Large language models (LLMs) are developing rapidly and have been widely applied in intelligent question answering, knowledge retrieval, education, healthcare, enterprise services, and other fields. However, LLMs still exhibit limitations i…
- HIACS: A High-Performance Hybrid Index Structure Combining ART and Skip List for Non- Volatile Memory Storage DevicesJunbao Song, Derong Shen, Tiezheng Nie, Yue Kou et al. · Data Science and Engineering · Sep 8, 2026
Non-Volatile Memory (NVM) offers nanosecond latency and data persistence, enabling new index designs for large-scale key-value stores. However, its write asymmetry (high write latency, write amplification) and limited bandwidth challenge ex…
- RAG-basierte SQL-Agenten im Unternehmenseinsatz: Architektur, Evaluation und praktische Implikationen für einen demokratisierten DatenbankzugriffDavid Bausch, Sven Keller, Christian Leyh · HMD Praxis der Wirtschaftsi... · Sep 7, 2026
Zusammenfassung Der Zugriff auf Unternehmensdaten über natürlichsprachliche Anfragen verspricht eine Demokratisierung der Datenbankinteraktion für nicht-technische Nutzer. Dieser Beitrag untersucht die Möglichkeiten und Grenzen von Text-to-…
- A large language model-enhanced knowledge graph framework for text-implied public health policy gap screening: digital health executability, behavioral accessibility, and service-support coverageXinyi Wang, Jiao Lu · Frontiers in Public Health · Sep 7, 2026
Screening for text-implied structural gaps in policy documents is an important component of public health policy review, particularly when implementation relies on online portals, digital identity verification, remote-care platforms, or sel…
- A review of the development, training, and application scenarios of multimodal large models for construction engineeringZhansheng Liu, Hao Zhou, Yungui Li, Meihao Zhu et al. · Engineering Construction & ... · Sep 7, 2026
Purpose To address fragmented research and the lack of integrated development frameworks for multimodal large models (MLMs) in construction engineering, this study employs a systematic literature review approach and proposes a structured fr…
- RG-RAGJamiu T. Suleiman · Zenodo (CERN European Organ... · Sep 6, 2026
This archive contains the code accompanying “Enhancing the Reliability of Retrieval-Augmented Generation for Personalized Language Models via Rationale Quality Modeling”. RG-RAG improves retrieval-augmented generation through quality-select…
- A retrieval-augmented automated stakeholder for requirements elicitation education: a comparative studyManal Binkhonain, Ohoud Alharbi · Requirements Engineering · Sep 6, 2026
- Cross-Lingual Indirect Prompt Injection Across Retrieval, Reranking, And Generation In Multilingual RAGFauzi Bondan Prihananto, Erlangga Bayu Yudho Prakoso, Aprilisa Arum Sari, Tomy Anugrah Islami · Journal Of Computer Science... · Sep 6, 2026
External evidence can make retrieval-augmented generation (RAG) more informative, yet retrieved passages also provide a path for adversarial instructions to enter the model context. We examine that path in an English-Indonesian RAG system a…
- RG-RAGJamiu T. Suleiman · Zenodo (CERN European Organ... · Sep 6, 2026
This archive contains the code accompanying “Enhancing the Reliability of Retrieval-Augmented Generation for Personalized Language Models via Rationale Quality Modeling”. RG-RAG improves retrieval-augmented generation through quality-select…
- GCF-RAG: Graph context fusion-based RAG framework for industrial equipment operation and maintenanceChengxuan Ge, Xiaobin Xu, Lingjun Dong, Zhenjie Zhang et al. · Advanced Engineering Inform... · Sep 5, 2026
- A Study: Architecture of Retrieval-Augmented Generation (RAG) Integrating Orchestration and Multi-Tiered EvaluationDr. V. S. Tondre Ms. V. V. Thakare · Zenodo (CERN European Organ... · Sep 5, 2026