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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 4976–5000 of 14297 papers

TitleStatusHype
ICAR: Image-based Complementary Auto Reasoning—0
Hitting the High-Dimensional Notes: An ODE for SGD learning dynamics on GLMs and multi-index models—0
Towards Filling the Gap in Conversational Search: From Passage Retrieval to Conversational Response GenerationCode0
A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings—0
Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluationCode0
Visually-Aware Context Modeling for News Image CaptioningCode0
RSpell: Retrieval-augmented Framework for Domain Adaptive Chinese Spelling CheckCode1
Pre-training with Large Language Model-based Document Expansion for Dense Passage Retrieval—0
ALIP: Adaptive Language-Image Pre-training with Synthetic CaptionCode1
Integrating Visual and Semantic Similarity Using Hierarchies for Image RetrievalCode0
Phase Retrieval with Background Information: Decreased References and Efficient Methods—0
Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System—0
Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions—0
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain ConversationCode1
Ranking-aware Uncertainty for Text-guided Image Retrieval—0
MVMR: A New Framework for Evaluating Faithfulness of Video Moment Retrieval against Multiple DistractorsCode0
Max-affine regression via first-order methods—0
Teach LLMs to Personalize -- An Approach inspired by Writing Education—0
Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation—0
RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language ModelsCode0
Prompt Switch: Efficient CLIP Adaptation for Text-Video RetrievalCode1
Vision-Language Dataset DistillationCode1
BIRP: Bitcoin Information Retrieval Prediction Model Based on Multimodal Pattern Matching—0
Large Language Models for Information Retrieval: A SurveyCode2
Diffusion Based Augmentation for Captioning and Retrieval in Cultural HeritageCode0
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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