RAG
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Benchmarks
Most implemented
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
ColPali: Efficient Document Retrieval with Vision Language Models
Retrieval-Augmented Generation for Large Language Models: A Survey
Papers
A Survey of Context Engineering for Large Language Models
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a formal discipline that transcends simple …
RAGRetrievalRetrieval-augmented GenerationSurveyDeveloping Visual Augmented Q&A System using Scalable Vision Embedding Retrieval & Late Interaction Re-ranker
Traditional information extraction systems face challenges with text only language models as it does not consider infographics (visual elements of information) such as tables, charts, images etc. often used to convey com…
RAGRetrievalLeveraging RAG-LLMs for Urban Mobility Simulation and Analysis
With the rise of smart mobility and shared e-mobility services, numerous advanced technologies have been applied to this field. Cloud-based traffic simulation solutions have flourished, offering increasingly realistic re…
Decision MakingRAGMIRIX: Multi-Agent Memory System for LLM-Based Agents
Although memory capabilities of AI agents are gaining increasing attention, existing solutions remain fundamentally limited. Most rely on flat, narrowly scoped memory components, constraining their ability to personalize…
RAGCLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs
Large language models (LLMs), including zero-shot and few-shot paradigms, have shown promising capabilities in clinical text generation. However, real-world applications face two key challenges: (1) patient data is highl…
ChunkingRAGRetrievalRetrieval-augmented Generation+1Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation
Large language models (LLMs) incorporated with Retrieval-Augmented Generation (RAG) have demonstrated powerful capabilities in generating counterspeech against misinformation. However, current studies rely on limited evi…
InformativenessMisinformationRAGRetrieval+1