SOTAVerified

Information Retrieval

Information retrieval is the task of ranking a list of documents or search results in response to a query

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Papers

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Showing 1576–1600 of 4740 papers

TitleStatusHype
JEPOO: Highly Accurate Joint Estimation of Pitch, Onset and Offset for Music Information Retrieval—0
BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language—0
A template-independent approach for information extraction in real estate documentsCode0
TReR: A Lightweight Transformer Re-Ranking Approach for 3D LiDAR Place Recognition—0
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer—0
Exploring the Practicality of Generative Retrieval on Dynamic Corpora—0
FARA: Future-aware Ranking Algorithm for Fairness OptimizationCode0
People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts—0
An Empirical Comparison of LM-based Question and Answer Generation Methods—0
The Search for Stability: Learning Dynamics of Strategic Publishers with Initial DocumentsCode0
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning—0
Referral Augmentation for Zero-Shot Information RetrievalCode0
Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and BenchmarkCode0
Fusion-in-T5: Unifying Document Ranking Signals for Improved Information RetrievalCode0
BM25 Query Augmentation Learned End-to-End—0
Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-rankerCode0
Knowledge Graphs Querying—0
Conversational Recommendation as Retrieval: A Simple, Strong Baseline—0
Differential Privacy with Random Projections and Sign Random Projections—0
REFinD: Relation Extraction Financial DatasetCode0
IR Models and the COVID-19 Pandemic: A Comparative Study of Performance and Challenges—0
CCT-Code: Cross-Consistency Training for Multilingual Clone Detection and Code Search—0
Exploring the Viability of Synthetic Query Generation for Relevance Prediction—0
How Does Generative Retrieval Scale to Millions of Passages?—0
Improving Toponym Resolution with Better Candidate Generation, Transformer-based Reranking, and Two-Stage ResolutionCode0
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All datasetsBSARDMS MARCOCQADupStackTREC-PMAmazonMSLR WEB30KMSMARCOMTEBNews HeadlinesOhsumed

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Two-tower Bi-Encoder (RoBERTa)Recall@10074.78—Unverified
2Siamese Bi-Encoder (RoBERTa)Recall@10071.63—Unverified
3BM25Recall@10051.33—Unverified
#ModelMetricClaimedVerifiedStatus
1RetroMAE v2MRR@1042.58—Unverified
2ConAE-256Time (ms)0.33—Unverified
3ConAE-128Time (ms)0.32—Unverified
#ModelMetricClaimedVerifiedStatus
1SGPT-BE-5.8BmAP@1000.16—Unverified
2TSDAEmAP@1000.15—Unverified
#ModelMetricClaimedVerifiedStatus
1hpipubcommoninfNDCG0.56—Unverified
2hpictallinfNDCG0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1MINDHR@300.32—Unverified
#ModelMetricClaimedVerifiedStatus
1Distilled NetworknDCG@100.53—Unverified
#ModelMetricClaimedVerifiedStatus
1RetroMAEMRR@100.42—Unverified
#ModelMetricClaimedVerifiedStatus
1SGPT-5.8B-msmarconDCG@1050.25—Unverified
#ModelMetricClaimedVerifiedStatus
1Information Retrieval + SVM1:1 Accuracy83.79—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT+CONCEPT FILTERNDCG0.25—Unverified