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 8326–8350 of 14297 papers

TitleStatusHype
ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating—0
GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models—0
GPT-3 Models are Few-Shot Financial Reasoners—0
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval—0
How Does Knowledge Selection Help Retrieval Augmented Generation?—0
Contextual Mood Analysis with Knowledge Graph Representation for Hindi Song Lyrics in Devanagari Script—0
Contextual Memory Trees—0
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG—0
Almanac: Retrieval-Augmented Language Models for Clinical Medicine—0
Google Landmark Retrieval 2021 Competition Third Place Solution—0
Contextual Media Retrieval Using Natural Language Queries—0
Good/Evil Reputation Judgment of Celebrities by LLMs via Retrieval Augmented Generation—0
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset—0
good4cir: Generating Detailed Synthetic Captions for Composed Image Retrieval—0
Gold Standard Online Debates Summaries and First Experiments Towards Automatic Summarization of Online Debate Data—0
Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review—0
Almanac Copilot: Towards Autonomous Electronic Health Record Navigation—0
GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval—0
GNN-Coder: Boosting Semantic Code Retrieval with Combined GNNs and Transformer—0
Contextualized Query Embeddings for Conversational Search—0
Async Learned User Embeddings for Ads Delivery Optimization—0
Adapting Large Language Models for Multi-Domain Retrieval-Augmented-Generation—0
A Birds Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges—0
GMM-Based Comprehensive Feature Extraction and Relative Distance Preservation For Few-Shot Cross-Modal Retrieval—0
GME: Improving Universal Multimodal Retrieval by Multimodal LLMs—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