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 3751–3800 of 14297 papers

TitleStatusHype
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?—0
HaluEval-Wild: Evaluating Hallucinations of Language Models in the WildCode0
Exploring LLM-based Agents for Root Cause Analysis—0
Bridging Language and Items for Retrieval and RecommendationCode3
FaaF: Facts as a Function for the evaluation of generated textCode0
Backtracing: Retrieving the Cause of the QueryCode2
Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection AttacksCode1
Unsupervised Multilingual Dense Retrieval via Generative Pseudo LabelingCode0
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal DatasetsCode0
Reliable, Adaptable, and Attributable Language Models with Retrieval—0
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer ModelCode0
Interactive Continual Learning: Fast and Slow ThinkingCode2
ChatCite: LLM Agent with Human Workflow Guidance for Comparative Literature Summary—0
DRAK: Unlocking Molecular Insights with Domain-Specific Retrieval-Augmented Knowledge in LLMs—0
LLM-Oriented Retrieval Tuner—0
Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation ModelsCode2
From Zero to Hero: How local curvature at artless initial conditions leads away from bad minima—0
SyllabusQA: A Course Logistics Question Answering DatasetCode0
Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models—0
Logic Rules as Explanations for Legal Case RetrievalCode0
Fine Tuning vs. Retrieval Augmented Generation for Less Popular KnowledgeCode0
Answerability in Retrieval-Augmented Open-Domain Question Answering—0
Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval—0
ReMatch: Retrieval Enhanced Schema Matching with LLMsCode0
GPTSee: Enhancing Moment Retrieval and Highlight Detection via Description-Based Similarity Features—0
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching—0
Selective Encryption using Segmentation Mask with Chaotic Henon Map for Multidimensional Medical Images—0
RAGged Edges: The Double-Edged Sword of Retrieval-Augmented Chatbots—0
Asymmetric Feature Fusion for Image Retrieval—0
Structure Similarity Preservation Learning for Asymmetric Image RetrievalCode0
Phase retrieval beyond the homogeneous object assumption for X-ray in-line holographic imaging—0
Tri-Modal Motion Retrieval by Learning a Joint Embedding Space—0
DFIN-SQL: Integrating Focused Schema with DIN-SQL for Superior Accuracy in Large-Scale Databases—0
Crimson: Empowering Strategic Reasoning in Cybersecurity through Large Language Models—0
Open Assistant Toolkit -- version 2Code1
Transcription and translation of videos using fine-tuned XLSR Wav2Vec2 on custom dataset and mBART—0
Dual Pose-invariant Embeddings: Learning Category and Object-specific Discriminative Representations for Recognition and Retrieval—0
LocalRQA: From Generating Data to Locally Training, Testing, and Deploying Retrieval-Augmented QA SystemsCode0
Hierarchical Indexing for Retrieval-Augmented Opinion SummarizationCode0
Zero-Shot Topic Classification of Column Headers: Leveraging LLMs for Metadata EnrichmentCode0
Aligning Language Models for Versatile Text-based Item Retrieval—0
A SOUND APPROACH: Using Large Language Models to generate audio descriptions for egocentric text-audio retrieval—0
Dual Operating Modes of In-Context LearningCode1
Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines—0
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality TeachersCode4
PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval—0
Retrieval-Augmented Generation for AI-Generated Content: A SurveyCode5
Hierarchical Multimodal Pre-training for Visually Rich Webpage UnderstandingCode1
RNNs are not Transformers (Yet): The Key Bottleneck on In-context RetrievalCode1
A Categorization of Complexity Classes for Information Retrieval and Synthesis Using Natural Logic—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