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

Showing 33263350 of 4740 papers

TitleStatusHype
Two-Stage Hashing for Fast Document Retrieval0
Two-Step SPLADE: Simple, Efficient and Effective Approximation of SPLADE0
Type-Supervised Domain Adaptation for Joint Segmentation and POS-Tagging0
UABCoRAL: A Preliminary study for Resolving the Scope of Negation0
UAlacant: Using Online Machine Translation for Cross-Lingual Textual Entailment0
UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)0
UDLex: Towards Cross-language Subcategorization Lexicons0
UEM-UC3M: An Ontology-based named entity recognition system for biomedical texts.0
Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval0
Ultra-Concise Multi-genre Summarisation of Web2.0: towards Intelligent Content Generation0
UlyssesNER-Br: A Corpus of Brazilian Legislative Documents for Named Entity Recognition0
UMBC\_EBIQUITY-CORE: Semantic Textual Similarity Systems0
UMCC\_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance0
UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation0
UNAL: Discriminating between Literal and Figurative Phrasal Usage Using Distributional Statistics and POS tags0
Unary and Binary Classification Approaches and their Implications for Authorship Verification0
Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data0
Uncertainty Detection in Hungarian Texts0
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity0
Uncovering Distributional Differences between Synonyms and Antonyms in a Word Space Model0
Understanding and Predicting Characteristics of Test Collections in Information Retrieval0
Understanding BERT Rankers Under Distillation0
Understanding, Categorizing and Predicting Semantic Image-Text Relations0
Understanding Mobile Search Task Relevance and User Behaviour in Context0
Understanding news story chains using information retrieval and network clustering techniques0
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Benchmark Results

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