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 5801–5850 of 14297 papers

TitleStatusHype
Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities—0
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions—0
Intelligent Director: An Automatic Framework for Dynamic Visual Composition using ChatGPT—0
MultiContrievers: Analysis of Dense Retrieval RepresentationsCode0
Universal Model in Online Customer Service—0
Background Denoising for Ptychography via Wigner Distribution Deconvolution—0
Fine-tuning CLIP Text Encoders with Two-step Paraphrasing—0
Inference for Regression with Variables Generated by AI or Machine Learning—0
CFIR: Fast and Effective Long-Text To Image Retrieval for Large CorporaCode0
Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models—0
Tug-of-War Between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models—0
From Keywords to Structured Summaries: Streamlining Scholarly Information Access—0
Assessing generalization capability of text ranking models in Polish—0
Federated Neural Graph Databases—0
UFO: a Unified and Flexible Framework for Evaluating Factuality of Large Language ModelsCode0
BIRCO: A Benchmark of Information Retrieval Tasks with Complex ObjectivesCode0
Science Checker Reloaded: A Bidirectional Paradigm for Transparency and Logical ReasoningCode0
Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks—0
Improving Video Corpus Moment Retrieval with Partial Relevance EnhancementCode0
Whispers in Grammars: Injecting Covert Backdoors to Compromise Dense Retrieval SystemsCode0
MORE: Multi-mOdal REtrieval Augmented Generative Commonsense Reasoning—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
Fine-Grained Modeling of Narrative Context: A Coherence Perspective via Retrospective Questions—0
Learning to Retrieve for Job Matching—0
ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance LabelingCode0
Event-aware Video Corpus Moment Retrieval—0
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language ModelsCode0
Sparse and Structured Hopfield NetworksCode0
The Effectiveness of Graph Contrastive Learning on Mathematical Information RetrievalCode0
Leveraging Translation For Optimal Recall: Tailoring LLM Personalization With User Profiles—0
Self-DC: When to Reason and When to Act? Self Divide-and-Conquer for Compositional Unknown Questions—0
Unlocking Insights: Semantic Search in Jupyter Notebooks—0
DINOBot: Robot Manipulation via Retrieval and Alignment with Vision Foundation Models—0
SoftQE: Learned Representations of Queries Expanded by LLMs—0
Stochastic Graph Heat Modelling for Diffusion-based Connectivity Retrieval—0
PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods—0
Towards Trustworthy Reranking: A Simple yet Effective Abstention MechanismCode0
FormulaReasoning: A Dataset for Formula-Based Numerical ReasoningCode0
Effective and Efficient Conversation Retrieval for Dialogue State Tracking with Implicit Text Summaries—0
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning—0
Unveiling the Magic: Investigating Attention Distillation in Retrieval-augmented Generation—0
BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidence—0
Cofca: A Step-Wise Counterfactual Multi-hop QA benchmark—0
Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge—0
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation—0
Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversational Search—0
TriSampler: A Better Negative Sampling Principle for Dense Retrieval—0
Standardize: Aligning Language Models with Expert-Defined Standards for Content GenerationCode0
Surprising Efficacy of Fine-Tuned Transformers for Fact-Checking over Larger Language Models—0
KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students—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