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Retrieval-augmented Generation

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Showing 476–500 of 2196 papers

TitleStatusHype
DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation—0
A Grounded Memory System For Smart Personal Assistants—0
How Does Knowledge Selection Help Retrieval Augmented Generation?—0
A Graph-Retrieval-Augmented Generation Framework Enhances Decision-Making in the Circular Economy—0
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG—0
Conversational Text Extraction with Large Language Models Using Retrieval-Augmented Systems—0
A Survey on Retrieval-Augmented Text Generation for Large Language Models—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency—0
TOBUGraph: Knowledge Graph-Based Retrieval for Enhanced LLM Performance Beyond RAG—0
Control Token with Dense Passage Retrieval—0
ControlNET: A Firewall for RAG-based LLM System—0
A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models—0
Dialogic Pedagogy for Large Language Models: Aligning Conversational AI with Proven Theories of Learning—0
A Survey on Knowledge-Oriented Retrieval-Augmented Generation—0
Controlled Retrieval-augmented Context Evaluation for Long-form RAG—0
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings—0
Conversation AI Dialog for Medicare powered by Finetuning and Retrieval Augmented Generation—0
A Survey on Retrieval-Augmented Text Generation—0
ConTReGen: Context-driven Tree-structured Retrieval for Open-domain Long-form Text Generation—0
CORAG: A Cost-Constrained Retrieval Optimization System for Retrieval-Augmented Generation—0
CoRAG: Collaborative Retrieval-Augmented Generation—0
A Survey of Query Optimization in Large Language Models—0
CORD: Balancing COnsistency and Rank Distillation for Robust Retrieval-Augmented Generation—0
A Comparative Study of DSL Code Generation: Fine-Tuning vs. Optimized Retrieval Augmentation—0
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