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 551–575 of 4740 papers

TitleStatusHype
Scalable Frame-based Construction of Sociocultural NormBases for Socially-Aware Dialogues—0
Streamlining Conformal Information Retrieval via Score Refinement—0
Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers—0
HATFormer: Historic Handwritten Arabic Text Recognition with Transformers—0
BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale—0
Unified Multimodal Interleaved Document Representation for Retrieval—0
CoLLAP: Contrastive Long-form Language-Audio Pretraining with Musical Temporal Structure Augmentation—0
Simplifying complex machine learning by linearly separable network embedding spaces—0
PairDistill: Pairwise Relevance Distillation for Dense RetrievalCode1
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis—0
Do Music Generation Models Encode Music Theory?Code1
ThreatGram 101 - Extreme Telegram Replies Data with Threat LevelsCode0
Customized Information and Domain-centric Knowledge Graph Construction with Large Language Models—0
Generative Retrieval Meets Multi-Graded Relevance—0
CBIDR: A novel method for information retrieval combining image and data by means of TOPSIS applied to medical diagnosis—0
Enhancing Structured-Data Retrieval with GraphRAG: Soccer Data Case Study—0
Disentangling Questions from Query Generation for Task-Adaptive Retrieval—0
Unsupervised Text Representation Learning via Instruction-Tuning for Zero-Shot Dense Retrieval—0
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment—0
Creating Healthy Friction: Determining Stakeholder Requirements of Job Recommendation ExplanationsCode0
IRSC: A Zero-shot Evaluation Benchmark for Information Retrieval through Semantic Comprehension in Retrieval-Augmented Generation ScenariosCode0
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA—0
Lessons Learned on Information Retrieval in Electronic Health Records: A Comparison of Embedding Models and Pooling Strategies—0
One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP TasksCode1
Multi-View Adaptive Contrastive Learning for Information Retrieval Based Fault Localization—0
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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