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 6051–6075 of 14297 papers

TitleStatusHype
Large Scale Multi-Lingual Multi-Modal Summarization DatasetCode0
VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval—0
SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted IndexesCode4
Improving Out-of-Distribution Generalization of Neural Rerankers with Contextualized Late Interaction—0
Joint Span Segmentation and Rhetorical Role Labeling with Data Augmentation for Legal Documents—0
UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal ModelingCode1
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking—0
Differentiable Outlier Detection Enable Robust Deep Multimodal AnalysisCode0
Sketch Less Face Image Retrieval: A New ChallengeCode1
Overview of the TREC 2022 Fair Ranking Track—0
MatKB: Semantic Search for Polycrystalline Materials Synthesis ProceduresCode0
Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models—0
Alloprof: a new French question-answer education dataset and its use in an information retrieval case studyCode0
CREDENCE: Counterfactual Explanations for Document Ranking—0
Is Multimodal Vision Supervision Beneficial to Language?Code0
Unified Vision-Language Representation Modeling for E-Commerce Same-Style Products Retrieval—0
Fast Gumbel-Max Sketch and its Applications—0
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning—0
A Hopfield-like model with complementary encodings of memories—0
Hierarchical Event Grounding—0
Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories—0
OPORP: One Permutation + One Random Projection—0
Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service SupportCode1
Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems From a Multi-task Perspective—0
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image RetrievalCode1
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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