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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5301–5325 of 14297 papers

TitleStatusHype
Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations—0
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models—0
Fast Interactive Image Retrieval using large-scale unlabeled data—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
FastHybrid: A Hybrid Model for Efficient Answer Selection—0
Fine-tuning the SwissBERT Encoder Model for Embedding Sentences and Documents—0
Comparing Traditional and LLM-based Search for Image Geolocation—0
FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation—0
Fast Gumbel-Max Sketch and its Applications—0
FinSage: A Multi-aspect RAG System for Financial Filings Question Answering—0
Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization—0
COIN: Co-Cluster Infomax for Bipartite Graphs—0
Comparison of the effects of investor attention using search volume data before and after mobile device popularization—0
Good/Evil Reputation Judgment of Celebrities by LLMs via Retrieval Augmented Generation—0
Fast Generating A Large Number of Gumbel-Max Variables—0
Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval—0
First Place Solution of 2023 Global Artificial Intelligence Technology Innovation Competition Track 1—0
First Steps towards the Semi-automatic Development of a Wordformation-based Lexicon of Latin—0
First Token Probability Guided RAG for Telecom Question Answering—0
FiSTECH: Financial Style Transfer to Enhance Creativity without Hallucinations in LLMs—0
Competitive Retrieval: Going Beyond the Single Query—0
FIT-RAG: Black-Box RAG with Factual Information and Token Reduction—0
Complementarity, F-score, and NLP Evaluation—0
Fixing Data That Hurts Performance: Cascading LLMs to Relabel Hard Negatives for Robust Information Retrieval—0
Asking Clarifying Questions Based on Negative Feedback in Conversational Search—0
Show:102550
← PrevPage 213 of 572Next →
All datasetsQuora Question PairsHotpotQANatural QuestionsOK-VQAInfoSeekMVKPolyvorePubMedQAPubMedQA corpus with metadataToolLensคลิปไวรัล!! ไอซ์ ปรีชญา ลืมปิดไลฟ์สดตอนอาบน้ำ ถูกแชร์กระหึ่มเน็ต

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