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 76–100 of 14297 papers

TitleStatusHype
Multimodal Whole Slide Foundation Model for PathologyCode4
LLM2CLIP: Powerful Language Model Unlocks Richer Visual RepresentationCode4
TabM: Advancing Tabular Deep Learning with Parameter-Efficient EnsemblingCode4
When Does Perceptual Alignment Benefit Vision Representations?Code4
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality DocumentsCode4
EasyRAG: Efficient Retrieval-Augmented Generation Framework for Automated Network OperationsCode4
DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming HeadsCode4
Evaluating Pre-trained Convolutional Neural Networks and Foundation Models as Feature Extractors for Content-based Medical Image RetrievalCode4
Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented GenerationCode4
Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up QuestionsCode4
Goldfish: Vision-Language Understanding of Arbitrarily Long VideosCode4
Halu-J: Critique-Based Hallucination JudgeCode4
Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingCode4
COS-Mix: Cosine Similarity and Distance Fusion for Improved Information RetrievalCode4
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attentionCode4
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt OptimizationCode4
Long-CLIP: Unlocking the Long-Text Capability of CLIPCode4
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality TeachersCode4
Chain-of-Discussion: A Multi-Model Framework for Complex Evidence-Based Question AnsweringCode4
2D Matryoshka Sentence EmbeddingsCode4
Benchmarking Retrieval-Augmented Generation for MedicineCode4
Generative Representational Instruction TuningCode4
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question AnsweringCode4
Bryndza at ClimateActivism 2024: Stance, Target and Hate Event Detection via Retrieval-Augmented GPT-4 and LLaMACode4
Retrieval-Augmented Generation for Large Language Models: A SurveyCode4
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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