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Retrieval-augmented Generation

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Showing 2126–2150 of 2196 papers

TitleStatusHype
Enhancing Multilingual Information Retrieval in Mixed Human Resources Environments: A RAG Model Implementation for Multicultural Enterprise—0
A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language ModelsCode0
Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods—0
A Reliable Knowledge Processing Framework for Combustion Science using Foundation Models—0
Dynamic In-Context Learning from Nearest Neighbors for Bundle Generation—0
ESGReveal: An LLM-based approach for extracting structured data from ESG reports—0
Privacy-Preserved Neural Graph DatabasesCode0
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLPCode0
Parameter Efficient Tuning Allows Scalable Personalization of LLMs for Text Entry: A Case Study on Abbreviation Expansion—0
Experimenting with Large Language Models and vector embeddings in NASA SciX—0
RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios—0
GEAR-Up: Generative AI and External Knowledge-based Retrieval Upgrading Scholarly Article Searches for Systematic Reviews—0
Dynamic Retrieval-Augmented Generation—0
Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge GapsCode0
Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping—0
DevBots can co-design APIs—0
Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs—0
Context Tuning for Retrieval Augmented Generation—0
PaperQA: Retrieval-Augmented Generative Agent for Scientific Research—0
A Glitch in the Matrix? Locating and Detecting Language Model Grounding with FakepediaCode0
IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions—0
SenTest: Evaluating Robustness of Sentence Encoders—0
How to Build an AI Tutor That Can Adapt to Any Course Using Knowledge Graph-Enhanced Retrieval-Augmented Generation (KG-RAG)—0
Novel Preprocessing Technique for Data Embedding in Engineering Code Generation Using Large Language Model—0
Minimizing Factual Inconsistency and Hallucination in Large Language Models—0
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