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Retrieval-augmented Generation

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Showing 1776–1800 of 2196 papers

TitleStatusHype
Golden-Retriever: High-Fidelity Agentic Retrieval Augmented Generation for Industrial Knowledge Base—0
Unipa-GPT: Large Language Models for university-oriented QA in ItalianCode0
AuditNet: A Conversational AI-based Security Assistant [DEMO]—0
Adversarial Databases Improve Success in Retrieval-based Large Language Models—0
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities—0
Retrieval-Augmented Generation for Natural Language Processing: A Survey—0
PRAGyan -- Connecting the Dots in Tweets—0
Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach—0
Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical TasksCode0
Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models—0
Explainable Biomedical Hypothesis Generation via Retrieval Augmented Generation enabled Large Language Models—0
EchoSight: Advancing Visual-Language Models with Wiki Knowledge—0
Optimizing Query Generation for Enhanced Document Retrieval in RAG—0
Crafting the Path: Robust Query Rewriting for Information Retrieval—0
Better RAG using Relevant Information GainCode0
Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation—0
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting—0
Evaluation of RAG Metrics for Question Answering in the Telecom Domain—0
Knowledge and Aptitude Augmented Generation: Adaptive Multi-Turn Interaction in LLM SystemsCode0
Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together—0
Integrating AI Tutors in a Programming Course—0
GenSco: Can Question Decomposition based Passage Alignment improve Question Answering?—0
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond—0
Document-level Clinical Entity and Relation Extraction via Knowledge Base-Guided Generation—0
Context Embeddings for Efficient Answer Generation in RAG—0
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