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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 351–375 of 14297 papers

TitleStatusHype
CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents—0
FreeKV: Boosting KV Cache Retrieval for Efficient LLM Inference—0
TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis—0
PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented GenerationCode0
Enhancing Large Language Models with Reward-guided Tree Search for Knowledge Graph Question and Answering—0
Contrastive Alignment with Semantic Gap-Aware Corrections in Text-Video RetrievalCode0
LightRetriever: A LLM-based Hybrid Retrieval Architecture with 1000x Faster Query InferenceCode1
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering—0
Neuro-Symbolic Query CompilerCode1
Let's have a chat with the EU AI Act—0
ELITE: Embedding-Less retrieval with Iterative Text ExplorationCode1
Telco-oRAG: Optimizing Retrieval-augmented Generation for Telecom Queries via Hybrid Retrieval and Neural Routing—0
Unveiling Knowledge Utilization Mechanisms in LLM-based Retrieval-Augmented Generation—0
Demystifying and Enhancing the Efficiency of Large Language Model Based Search AgentsCode2
EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation—0
THELMA: Task Based Holistic Evaluation of Large Language Model Applications-RAG Question Answering—0
MIRACL-VISION: A Large, multilingual, visual document retrieval benchmark—0
CRISP: Clustering Multi-Vector Representations for Denoising and Pruning—0
The Future is Sparse: Embedding Compression for Scalable Retrieval in Recommender SystemsCode1
Search and Refine During Think: Autonomous Retrieval-Augmented Reasoning of LLMsCode2
Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models—0
mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge GraphsCode1
SubGCache: Accelerating Graph-based RAG with Subgraph-level KV Cache—0
Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate—0
Enhancing Low-Resource Minority Language Translation with LLMs and Retrieval-Augmented Generation for Cultural Nuances—0
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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