SOTAVerified

Retrieval-augmented Generation

Papers

Showing 326350 of 2196 papers

TitleStatusHype
NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question AnsweringCode1
Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)Code1
MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation SystemsCode1
Dubo-SQL: Diverse Retrieval-Augmented Generation and Fine Tuning for Text-to-SQLCode1
ECG Semantic Integrator (ESI): A Foundation ECG Model Pretrained with LLM-Enhanced Cardiological TextCode1
DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMsCode1
mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge GraphsCode1
MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning AttacksCode1
Do RAG Systems Cover What Matters? Evaluating and Optimizing Responses with Sub-Question CoverageCode1
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented GenerationCode1
Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMsCode1
Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented GenerationCode1
Metacognitive Retrieval-Augmented Large Language ModelsCode1
Efficient fine-tuning methodology of text embedding models for information retrieval: contrastive learning penalty (clp)Code1
FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMsCode1
Block-Attention for Efficient RAGCode1
Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-GenerationCode1
ECoRAG: Evidentiality-guided Compression for Long Context RAGCode1
Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial TrainingCode1
MetaGen Blended RAG: Higher Accuracy for Domain-Specific Q&A Without Fine-TuningCode1
"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented GenerationCode1
Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation SystemsCode1
Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience ReportCode1
MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAGCode1
Long Context vs. RAG for LLMs: An Evaluation and RevisitsCode1
Show:102550
← PrevPage 14 of 88Next →

No leaderboard results yet.