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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 3901–3925 of 14297 papers

TitleStatusHype
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation—0
BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidence—0
Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge—0
Cofca: A Step-Wise Counterfactual Multi-hop QA benchmark—0
Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term ConversationsCode1
Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversational Search—0
Unveiling the Magic: Investigating Attention Distillation in Retrieval-augmented Generation—0
TriSampler: A Better Negative Sampling Principle for Dense Retrieval—0
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning—0
EVOR: Evolving Retrieval for Code GenerationCode2
Surprising Efficacy of Fine-Tuned Transformers for Fact-Checking over Larger Language Models—0
Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges—0
Metacognitive Retrieval-Augmented Large Language ModelsCode1
BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models—0
Visual In-Context Learning for Large Vision-Language Models—0
When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval AugmentationCode1
Exploring ChatGPT for Next-generation Information Retrieval: Opportunities and Challenges—0
GenDec: A robust generative Question-decomposition method for Multi-hop reasoning—0
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering—0
Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement—0
FinTral: A Family of GPT-4 Level Multimodal Financial Large Language ModelsCode0
Dense Passage Retrieval: Is it Retrieving?—0
Distillation Enhanced Generative RetrievalCode2
Retrieve Only When It Needs: Adaptive Retrieval Augmentation for Hallucination Mitigation in Large Language Models—0
Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond—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