SOTAVerified

Retrieval

A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.

Papers

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Showing 26–50 of 14297 papers

TitleStatusHype
SGLang: Efficient Execution of Structured Language Model ProgramsCode6
Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language ModelsCode6
RAGAS: Automated Evaluation of Retrieval Augmented GenerationCode6
Extending Context Window of Large Language Models via Positional InterpolationCode6
Gorilla: Large Language Model Connected with Massive APIsCode6
Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion ModelsCode6
Semi-Parametric Neural Image SynthesisCode6
RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query ParallelismCode5
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation ModelsCode5
Benchmarking the Myopic Trap: Positional Bias in Information RetrievalCode5
ZeroSearch: Incentivize the Search Capability of LLMs without SearchingCode5
TrustRAG: An Information Assistant with Retrieval Augmented GenerationCode5
Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGCode5
MiniRAG: Towards Extremely Simple Retrieval-Augmented GenerationCode5
Search-o1: Agentic Search-Enhanced Large Reasoning ModelsCode5
Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge TasksCode5
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and InferenceCode5
SCBench: A KV Cache-Centric Analysis of Long-Context MethodsCode5
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMsCode5
KBLaM: Knowledge Base augmented Language ModelCode5
rerankers: A Lightweight Python Library to Unify Ranking MethodsCode5
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented GenerationCode5
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalCode5
BM25S: Orders of magnitude faster lexical search via eager sparse scoringCode5
Make Your LLM Fully Utilize the ContextCode5
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second183.53—Unverified
2ElasticsearchQueries per second21.8—Unverified
3BM25-PTQueries per second6.49—Unverified
4Rank-BM25Queries per second1.18—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second20.88—Unverified
2ElasticsearchQueries per second7.11—Unverified
3Rank-BM25Queries per second0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second41.85—Unverified
2ElasticsearchQueries per second12.16—Unverified
3Rank-BM25Queries per second0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FLMRRecall@589.32—Unverified
2RA-VQARecall@582.84—Unverified
#ModelMetricClaimedVerifiedStatus
1PreFLMRRecall@562.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-KIStext-to-video Mean Rank30—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4OutfitRecall@57.59—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1COLTCOMP@84.55—Unverified
#ModelMetricClaimedVerifiedStatus
1hello0L1,121,222—Unverified