Relevant bibliographies by topics / RAG Models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'RAG Models'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "RAG Models"

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Glynn, Rebecca, and Craig Bassing. "Elucidating the Role of NEMO and SpiC in DNA Double Strand Break Induced Inhibition of V(D)J Recombination." Journal of Immunology 204, no. 1_Supplement (2020): 223.12. http://dx.doi.org/10.4049/jimmunol.204.supp.223.12.

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Abstract V(D)J recombination is regulated such that most lymphocytes assemble and express an antigen receptor from only one allele (allelic exclusion). In pre-B cells, RAG-induced DNA double strand breaks (DSBs) at Igκ loci signal via ATM to rapidly repress Rag1/2 transcription, inhibit accessibility of Igk loci, and limit V recombination. We hypothesize that RAG DSB-induced repression of Rag1/2 is critical to transiently limit V recombination, ensure allelic exclusion, and inhibit oncogenic Ig translocations. Fittingly, Atm−/− mice have higher frequencies of developing B cells with RAG DSBs a
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Researcher. "ADVANCING GENERATIVE AI WITH RAG: ENHANCING RELEVANCE, CREATIVITY, AND RELIABILITY IN LANGUAGE MODELS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 4 (2024): 321–29. https://doi.org/10.5281/zenodo.13234310.

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This comprehensive article delves into the emergence and potential of RAG (Retrieve, Augment, Generate) models as a significant advancement in Large Language Models (LLMs). The article examines how RAG models address key limitations of traditional LLMs by integrating dynamic knowledge retrieval mechanisms, enhancing relevance, creativity, and reliability in AI-generated content. It discusses the three-component architecture of RAG models, their ability to mitigate hallucinations, and their applications across various domains. The article also outlines future prospects, including multilingual c
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Dietrich, N., and B. Stubbert. "P.121 Bridging the evidence gap: RAG-enabled LLMs in neuroimaging decision support." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 52, s1 (2025): S44. https://doi.org/10.1017/cjn.2025.10274.

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Background: Large language models (LLMs) offer potential for clinical decision support but may not fully adhere to current guidelines. Retrieval-augmented generation (RAG) may address this gap by dynamically incorporating external knowledge. This study evaluated LLM adherence with and without RAG to Canadian neuroimaging guidelines. Methods: A novel RAG framework was developed that integrated Canadian Association of Radiologists (CAR) Diagnostic Imaging Referral Guidelines with GPT-4o and o1 models. Clinical scenarios were curated to represent various central nervous system conditions, such as
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Amugongo, Lameck Mbangula, Pietro Mascheroni, Steven Brooks, Stefan Doering, and Jan Seidel. "Retrieval augmented generation for large language models in healthcare: A systematic review." PLOS Digital Health 4, no. 6 (2025): e0000877. https://doi.org/10.1371/journal.pdig.0000877.

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Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate (“hallucinated”) content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and e
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Chen, Jiawei, Hongyu Lin, Xianpei Han, and Le Sun. "Benchmarking Large Language Models in Retrieval-Augmented Generation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 16 (2024): 17754–62. http://dx.doi.org/10.1609/aaai.v38i16.29728.

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Retrieval-Augmented Generation (RAG) is a promising approach for mitigating the hallucination of large language models (LLMs). However, existing research lacks rigorous evaluation of the impact of retrieval-augmented generation on different large language models, which make it challenging to identify the potential bottlenecks in the capabilities of RAG for different LLMs. In this paper, we systematically investigate the impact of Retrieval-Augmented Generation on large language models. We analyze the performance of different large language models in 4 fundamental abilities required for RAG, in
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Grabuloski, Marko, Aleksandar Karadimce, and Anis Sefidanoski. "Enhancing Language Models with Retrieval-Augmented Generation A Comparative Study on Performance." WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS 22 (April 2, 2025): 272–97. https://doi.org/10.37394/23209.2025.22.23.

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Retrieval-Augmented Generation (RAG) is a powerful technique that enhances the capabilities of Large Language Models (LLMs) by integrating information retrieval with text generation. By accessing and incorporating relevant external knowledge, RAG systems address the limitations of traditional LLMs, such as memory constraints and the inability to access up-to-date information. This research explores the implementation and evaluation of RAG systems, focusing on their potential to improve the accuracy and relevance of LLM responses. It investigates the impact of different LLM types (causal, quest
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Siriwardhana, Shamane, Rivindu Weerasekera, Elliott Wen, Tharindu Kaluarachchi, Rajib Rana, and Suranga Nanayakkara. "Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering." Transactions of the Association for Computational Linguistics 11 (2023): 1–17. http://dx.doi.org/10.1162/tacl_a_00530.

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Abstract Retrieval Augment Generation (RAG) is a recent advancement in Open-Domain Question Answering (ODQA). RAG has only been trained and explored with a Wikipedia-based external knowledge base and is not optimized for use in other specialized domains such as healthcare and news. In this paper, we evaluate the impact of joint training of the retriever and generator components of RAG for the task of domain adaptation in ODQA. We propose RAG-end2end, an extension to RAG that can adapt to a domain-specific knowledge base by updating all components of the external knowledge base during training.
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Murtiyoso, Murtiyoso, Imam Tahyudin, and Berlilana Berlilana. "A Systematic Review of Retrieval-Augmented Generation for Enhancing Domain-Specific Knowledge in Large Language Models." Sinkron 9, no. 2 (2025): 969–77. https://doi.org/10.33395/sinkron.v9i2.14824.

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This literature review examines the use of Retrieval-Augmented Generation (RAG) in enhancing Large Language Models (LLM) for domain-specific knowledge. RAG integrates retrieval techniques with generative models to access external knowledge sources, addressing the limitations of LLMs in handling specialized information. By leveraging external data, RAG improves the accuracy and relevance of generated content, making it particularly useful in fields that require detailed and up-to-date knowledge. This review highlights the effectiveness of RAG in overcoming challenges such as data sparsity and t
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DeBellis, Michael, Nivedita Dutta, Jacob Gino, and Aadarsh Balaji. "Integrating Ontologies and Large Language Models to Implement Retrieval Augmented Generation." Applied Ontology 19, no. 4 (2024): 389–407. https://doi.org/10.1177/15705838241296446.

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Large language models (LLMs) have captured the imagination of the public and the technical community. As powerful as they are they have problems that prohibit their use for highly skilled users. These issues are hallucinations, bias, black-box reasoning, and lack of domain depth. One of the most popular architectures to alleviate these problems is retrieval augmented generation (RAG). In a RAG architecture, the LLM is utilized to generate vectors and to parse and generate natural language. The knowledge base for a RAG architecture is typically a set of documents focused on a particular type of
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Pingua, Bhagyajit, Adyakanta Sahoo, Meenakshi Kandpal, et al. "Medical LLMs: Fine-Tuning vs. Retrieval-Augmented Generation." Bioengineering 12, no. 7 (2025): 687. https://doi.org/10.3390/bioengineering12070687.

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Large language models (LLMs) are trained on huge datasets, which allow them to answer questions from various domains. However, their expertise is confined to the data that they were trained on. In order to specialize LLMs in niche domains like healthcare, various training methods can be employed. Two of these commonly known approaches are retrieval-augmented Generation and model fine-tuning. Five models—Llama-3.1-8B, Gemma-2-9B, Mistral-7B-Instruct, Qwen2.5-7B, and Phi-3.5-Mini-Instruct—were fine-tuned on healthcare data. These models were trained using three distinct approaches: retrieval-aug
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Dissertations / Theses on the topic "RAG Models"

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Schaeffer, Marion. "Towards efficient Knowledge Graph-based Retrieval Augmented Generation for conversational agents." Electronic Thesis or Diss., Normandie, 2025. http://www.theses.fr/2025NORMIR06.

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Les agents conversationnels se sont largement répandus ces dernières années. Aujourd'hui, ils ont dépassé leur objectif initial de simuler une conversation avec un programme informatique et sont désormais des outils précieux pour accéder à l'information et effectuer diverses tâches, allant du service client à l'assistance personnelle. Avec l'essor des modèles génératifs et des grands modèles de langage (LLM), les capacités des agents conversationnels ont été décuplées. Cependant, ils sont désormais sujets à des hallucinations, générant ainsi des informations erronées. Une technique populaire p
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Pontes, Paulo Rógenes Monteiro. "Comparação de modelos hidrodinâmicos simplificados de propagação de vazão em rios e canais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/35350.

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Esse trabalho identificou, testou e aprimorou modelos de propagação de vazão simplificados a fim de verificar as vantagens e desvantagens dos modelos. As soluções apresentadas por esses modelos foram testadas com um modelo hidrodinâmico completo, considerado nesse trabalho como resultados ideias. Os modelos hidrodinâmicos simplificados testados foram: Um modelo não linear de Onda Cinemática, o modelo Muskingum-Cunge linear, duas versões do modelo Muskingum-Cunge não linar, o modelo Muskingum-Cunge modificado por Todini e o modelo IPHS1. O modelo hidrodinâmico completo utilizado nesse trabalho
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Ruckert, Mariana Tannús. "Investigação do papel da ubiquitina-ligase HUWE1 na modulação da via de sinalização RAS em modelos leucêmicos." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/17/17135/tde-24042018-173652/.

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A via RAS/RAF/MEK/ERK é frequentemente hiperativada em diversos tumores. Em leucemias sua ativação pode ocorrer, dentre outros mecanismos, a partir de mutações pontuais nos genes da família RAS, que são relevantes nas leucemias linfóide e mielóide agudas (LLA e LMA), ou a partir da atividade da tirosina-quinase BCR-ABL, que é responsável por promover a tumorigênese na leucemia mielóide crônica (LMC) e em alguns casos de LLA. A hiperativação dessa via estimula a proliferação celular e, consequentemente, a produção de espécies reativas de oxigênio (ROS), que é um dos principais mecanismos envolv
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Acheampong, Josephine. "Green Financing: Financing Circular Economy Companies : Case Studies of Ragn-Sellsföretagen AB and Inrego AB." Thesis, KTH, Entreprenörskap och Innovation, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188677.

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The circular economy (CE) has been identified as a catalyst in sustainable development and economic growth that has the potential to move society from the traditional linear model of resource consumption in the form of take-make-waste to an innovative circular model in the form of reduce-reuse-recycle. Transitioning from the linear economy to the CE requires changes in four areas: material and product design, business models, global reverse networks and enabling business environments. This study considers the financing needs of CE companies as a result of business model changes. Through the ca
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Xiao, Feipeng. "Development of fatigue predictive models of rubberized asphalt concrete (RAC) containing reclaimed asphalt pavement (RAP) mixtures." Connect to this title online, 2006. http://etd.lib.clemson.edu/documents/1171902609/.

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Felix, Francisco HÃlder Cavalcante. "Rat brain Walker tumor implantation model." Universidade Federal do CearÃ, 2001. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=34.

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Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico<br>CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior<br>The disabling effects of central nervous system (CNS) tumors are out of proportion to their low incidence. Theyâre second only to stroke as neurologic mortality causes. Brain metastases are the commonest intracranial tumors in adults, almost 10 times more frequent than primary brain tumors. Their diagnosis and treatment have met significant advances, although much more research about drug resistance and new treatment modalities are needed. New and even better brain tu
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Henzler, Thomas. "Visible-Rat-Model: ein digitales anatomisches Muskel-Knochen-Modell der hinteren Extremität der Ratte." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:289-vts-60581.

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Oiso, Yutaka, Hiroshi Nagasaki, and Hisashi Yokoi. "Transgenic rat models of vasopressin overexpression." Nagoya University School of Medicine, 2003. http://hdl.handle.net/2237/5393.

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Si-Hoe, San Ling. "The utility of transgenic rat models." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325801.

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Brosnan, Mary Julia. "Experimental models of cardiomyopathy in the rat." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.253329.

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Books on the topic "RAG Models"

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(Firm), Bonhams. Deans rag book collection, dolls, teddy bears and related pieces: [auction] Tuesday 10 December 2002 ... ; Toys, trains, diecast, models and live steam : [auction] Wednesday 11 December 2002 .... Bonhams, 2002.

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Janus and Fondazione Marconi arte moderna e contemporanea, eds. Man Ray: Models. C. Cambi, 2013.

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1959-, Rigalli Alfredo, and Di Loreto, Veronica Elina, 1968-, eds. Experimental surgical models in the laboratory rat. Taylor & Francis, 2009.

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Anjela, Schischmanjan, and Wünsch Michaela, eds. Female Hiphop: Realness, Roots und Rap Models. Ventil, 2007.

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Katz, Jonathan I. Two populations and models of gamma-ray bursts. National Aeronautics and Space Administration, 1993.

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United States. National Aeronautics and Space Administration., ed. Integrating O&S models during conceptual design: PART II:reliability and maintainability model (RAM) user and maintenance manual. National Aeronautics and Space Administration, 1994.

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1954-, Gretz N., and Strauch M, eds. Experimental and genetic rat models of chronic renal failure. Karger, 1993.

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Hamiel, Daniel. Model ishiyuti be-mishnat ha-Rav Ḳuḳ. ḥ. mo. l., 1992.

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F, Mushotzky R., and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Spectral constraints on models of gas in clusters of galaxies. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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1956-, Matthews James, ed. High energy astrophysics: Models and observations from MeV to EeV. World Scientific, 1994.

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Book chapters on the topic "RAG Models"

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Singh, Bhawna. "Stop Hallucinations with RAG." In Building Applications with Large Language Models. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0569-1_5.

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Babaei Giglou, Hamed, Tilahun Abedissa Taffa, Rana Abdullah, et al. "Scholarly Question Answering Using Large Language Models in the NFDI4DataScience Gateway." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65794-8_1.

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AbstractThis paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4DS Gateway, as a foundational framework, offers a unified and intuitive interface for querying various scientific databases using federated search. The RAG-based scholarly QA, powered by a Large Language Model (LLM), facilitates dynamic interaction with search results, enhancing filtering capabilities and fostering a conversational engagement with the Gateway search. The effectiveness of both the Gateway and t
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Sudhir, Pratul, Sreya Suresh, and C. Thontadari. "Leveraging Agentic RAG to Reduce Hallucinations in Large Language Models." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4883-2_4.

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Feng, Kaiyue, Guangsheng Zhang, Huan Tian, et al. "RAGLeak: Membership Inference Attacks on RAG-Based Large Language Models." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-9101-2_8.

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Ampazis, Nicholas. "Improving RAG Quality for Large Language Models with Topic-Enhanced Reranking." In IFIP Advances in Information and Communication Technology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63215-0_6.

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Holvoet, Laura, Michael van Bekkum, and Aijse de Vries. "An Approach to Automated Instruction Generation with Grounding Using LLMs and RAG." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86489-6_23.

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Abstract Despite ongoing digitization in industry, many companies still work with paper instructions or ‘paper-on-glass’ solutions (e.g., PDF files on screens). In recent years, various digital work instruction (DWI) technologies have become available that provide shop-floor employees with information during their activities, e.g., sequences of instructions for tasks at hand. Engineering new instructions in these systems for new products or product variants is however expensive and time-consuming. To scale up, there is a need for methods to generate work instructions (semi) automatically. Rece
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Prakash, Vadlapudi Om, Jella Mahendar Rao, Ummenthala Sai, et al. "Chat with your recipe: An AI-powered culinary assistant using RAG and generative models." In Multi-Disciplinary Research and Sustainable Development. CRC Press, 2025. https://doi.org/10.1201/9781003675242-52.

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Otto, Wolfgang, Sharmila Upadhyaya, and Stefan Dietze. "Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65794-8_21.

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AbstractThis paper describes our participation in the Shared Task on Software Mentions Disambiguation (SOMD), with a focus on improving relation extraction in scholarly texts through generative Large Language Models (LLMs) using single-choice question-answering. The methodology prioritises the use of in-context learning capabilities of LLMs to extract software-related entities and their descriptive attributes, such as distributive information. Our approach uses Retrieval-Augmented Generation (RAG) techniques and LLMs for Named Entity Recognition (NER) and Attributive NER to identify relationsh
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Kouliaridis, Vasileios, Georgios Karopoulos, and Georgios Kambourakis. "Assessing the Effectiveness of LLMs in Android Application Vulnerability Analysis." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-85593-1_9.

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Abstract The increasing frequency of attacks on Android applications coupled with the recent popularity of large language models (LLMs) necessitates a comprehensive understanding of the capabilities of the latter in identifying potential vulnerabilities, which is key to mitigate the overall risk. To this end, the work at hand compares the ability of nine state-of-the-art LLMs to detect Android code vulnerabilities listed in the latest Open Worldwide Application Security Project (OWASP) Mobile Top 10. Each LLM was evaluated against an open dataset of over 100 vulnerable code samples, assessing
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EL Maazouzi, Qamar, Asmaâ Retbi, and Samir Bennani. "Optimizing Recommendation Systems in E-Learning: Synergistic Integration of Lang Chain, GPT Models, and Retrieval Augmented Generation (RAG)." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-77040-1_8.

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Conference papers on the topic "RAG Models"

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Zolfaghari, Vahid, Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda, and Alois Knoll. "Adopting RAG for LLM-Aided Future Vehicle Design." In 2024 2nd International Conference on Foundation and Large Language Models (FLLM). IEEE, 2024. https://doi.org/10.1109/fllm63129.2024.10852467.

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Kenneweg, Tristan, Philip Kenneweg, and Barbara Hammer. "RAGVAL: Automatic Dataset Creation and Evaluation for RAG Systems." In 2024 2nd International Conference on Foundation and Large Language Models (FLLM). IEEE, 2024. https://doi.org/10.1109/fllm63129.2024.10852482.

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Wood, Jacob, and Deepti Joshi. "Conflict-RAG: Understanding Evolving Conflicts Using Large Language Models." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825676.

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Agrawal, Garima, Tharindu Kumarage, Zeyad Alghamdi, and Huan Liu. "Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation." In 2024 2nd International Conference on Foundation and Large Language Models (FLLM). IEEE, 2024. https://doi.org/10.1109/fllm63129.2024.10852457.

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Darji, Abhishek, Fenil Kheni, Dhruvil Chodvadia, Parth Goel, Dweepna Garg, and Bankim Patel. "Enhancing Financial Risk Analysis using RAG-based Large Language Models." In 2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2024. https://doi.org/10.1109/icacrs62842.2024.10841711.

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Xia, Peng, Kangyu Zhu, Haoran Li, et al. "RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.62.

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He, Jacky, Guiran Liu, Binrong Zhu, Hanlu Zhang, Hongye Zheng, and Xiaokai Wang. "Context-Guided Dynamic Retrieval for Improving Generation Quality in RAG Models." In 2025 IEEE 7th International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2025. https://doi.org/10.1109/cisce65916.2025.11065272.

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Kamra, Vikas, Lakshya Gupta, Dhruv Arora, and Ashwin Kumar Yadav. "Evaluating Reinforcement Learning Based Models for Test Time Enhancement in RAG." In 2025 Second International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS). IEEE, 2025. https://doi.org/10.1109/icc-robins64345.2025.11086322.

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Islam, Shayekh Bin, Md Asib Rahman, K. S. M. Tozammel Hossain, Enamul Hoque, Shafiq Joty, and Md Rizwan Parvez. "Open-RAG: Enhanced Retrieval Augmented Reasoning with Open-Source Large Language Models." In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-emnlp.831.

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Gummadi, Venkata, Pamula Udayaraju, Venkata Rahul Sarabu, Chaitanya Ravulu, Dhanunjay Reddy Seelam, and S. Venkataramana. "Enhancing Communication and Data Transmission Security in RAG Using Large Language Models." In 2024 4th International Conference on Sustainable Expert Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63445.2024.10763024.

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Reports on the topic "RAG Models"

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Lang, Jonas. Multilevel Modeling in R: Basic and Advanced Methods. Instats Inc., 2023. http://dx.doi.org/10.61700/aac2dxlrxcebk469.

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The seminar teaches basic and intermediate multilevel techniques used in the social, health, and organizational sciences in an accessible manner. The course relies on the free software R and the modeling packages lme4 and nlme along with help functions and datasets from the multilevel library (Bliese, 2021). Topics include (1) aggregation models and the use of agreement and reliability statistics like the ICC1, ICC2, and rwg, (2) model specification and interpretation of “standard” multilevel models used in organizational research (data centering, random slopes, interaction effects), (3) graph
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Lang, Jonas. Multilevel Modeling in R: Basic and Advanced Methods + 1 Free Seminar. Instats Inc., 2022. http://dx.doi.org/10.61700/sw0snl2upp0gv469.

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The hands-on seminar teaches basic and intermediate multilevel techniques used in the social, health, and organizational sciences in an accessible manner. The course relies on the free software R and the modeling packages lme4 and nlme along with help functions and datasets from the multilevel library (Bliese, 2021). Topics include (1) aggregation models and the use of agreement and reliability statistics like the ICC1, ICC2, and rwg, (2) model specification and interpretation of “standard” multilevel models used in organizational research (data centering, random slopes, interaction effects),
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Acharya, Sushant, William Chen, Marco Del Negro, et al. Estimating HANK for Central Banks. Federal Reserve Bank of New York, 2023. http://dx.doi.org/10.59576/sr.1071.

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We provide a toolkit for efficient online estimation of heterogeneous agent (HA) New Keynesian (NK) models based on Sequential Monte Carlo methods. We use this toolkit to compare the out-of-sample forecasting accuracy of a prominent HANK model, Bayer et al. (2022), to that of the representative agent (RA) NK model of Smets and Wouters (2007, SW). We find that HANK’s accuracy for real activity variables is notably inferior to that of SW. The results for consumption in particular are disappointing since the main difference between RANK and HANK is the replacement of the RA Euler equation with th
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McDougall, Robert. Entropy Theory and RAS are Friends. GTAP Working Paper, 2000. http://dx.doi.org/10.21642/gtap.wp06.

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Presented at the Second Annual Conference on Global Economic Analysis Recent research in applications of entropy theory to matrix balancing problems in eco-nomics has put powerful new tools in the hands of data base developers, but overshadowed some previous findings. We recall earlier findings that the RAS is an entropy-theoretic model. Investigating the properties of a more recently proposed entropy-theoretic model, we find that in general the RAS remains preferable. We show further that the RAS can be obtained also as a generalised cross-entropy model. Finally, we present examples illus-tra
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Ávila Aravena, Bárbara, Laura Giles Álvarez, Cristhian Larrahondo, and Juan Carlos Vargas-Moreno. Marco territorial para el desarrollo inclusivo, sostenible y verde de la Región Amazónica Andina. Banco Interamericano de Desarrollo, 2024. http://dx.doi.org/10.18235/0005493.

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La Amazonía es uno de los recursos más complejos y ricos del mundo. Con sus 5,5 millones km2 de denso bosque tropical y 7,9 millones de km2 de cuenca, esta es una de las regiones más biodiversas y ricas del planeta. En Bolivia, Colombia, Ecuador, Perú y Venezuela la Región Amazónica Andina (RAA) estos 2,7 millones de km2 además son el hogar de aproximadamente 24,7 millones de personas, incluyendo más de 200 grupos indígenas conocidos. A pesar de sus ventajas y los esfuerzos invertidos, la RAA, su territorio y población, siguen estando expuestos a una serie de desafíos sociales, económicos y de
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Nur, Gazi Nazia. CoralAI: A RAG model to answer Coral-related queries. Iowa State University, 2024. https://doi.org/10.31274/cc-20250502-72.

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Li, Xiao, Fayang Ling, Wenchuan Qi, et al. Preclinical Evidence of Acupuncture on infarction size of Myocardial ischemia: A Systematic Review and Meta-Analysis of Animal Studies. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.6.0044.

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Review question / Objective: Whether acupuncture is effective for infarction size on myocardial ischemia rat models. Condition being studied: Myocardial ischemia is a typical pathological condition of coronary heart disease (CHD), which has been a global issue with high incidence and mortality. Myocardial infarction caused by myocardial ischemia leads to cardiac dysfunction, and the size of myocardial infarction also determines the recovery and prognosis of cardiac function. Acupuncture, a long history of traditional Chinese medicine, is widely used to treat symptoms like thoracalgia and palpi
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Griep, Anne E. Transgenic Rat Models for Breast Cancer Research. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/adb235877.

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Letcher, Theodore, Julie Parno, Zoe Courville, Lauren Farnsworth, and Jason Olivier. A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47122.

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A majority of snow radiative transfer models (RTMs) treat snow as a collection of idealized grains rather than an organized ice–air matrix. Here we present a generalized multi-layer photon-tracking RTM that simulates light reflectance and transmittance of snow based on X-ray micro- tomography images, treating snow as a coherent 3D structure rather than a collection of grains. The model uses a blended approach to expand ray-tracing techniques applied to sub-1 cm3 snow samples to snowpacks of arbitrary depths. While this framework has many potential applications, this study’s effort is focused o
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Lieng, Sotberg, and Brennodden. L51570 Energy Based Pipe-Soil Interaction Models. Pipeline Research Council International, Inc. (PRCI), 1988. http://dx.doi.org/10.55274/r0010091.

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The purpose of this project was to complete a handbook with practical design procedures for submarine pipeline on-bottom stability. The remaining part of the handbook was primarily a description of the interaction between non-trenched pipelines and the seabed where the pipelines were free to move under environmental loading. The objective of this project was to determine the lateral soil resistance forces on a pipeline moving cyclically during hydro-dynamic loading. To meet the goal, full-scale pipe-soil interaction tests were conducted. The models presented in this report are based on the res
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