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 1101–1125 of 4740 papers

TitleStatusHype
Modulating Language Model Experiences through Frictions—0
Context-augmented Retrieval: A Novel Framework for Fast Information Retrieval based Response Generation using Large Language Model—0
Evaluating D-MERIT of Partial-annotation on Information Retrieval—0
Database-Augmented Query Representation for Information Retrieval—0
Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback—0
IDentity with Locality: An ideal hash for gene sequence search—0
An End-to-End, Segmentation-Free, Arabic Handwritten Recognition Model on KHATT—0
Évaluation des capacités de réponse de larges modèles de langage (LLM) pour des questions d'historiens—0
TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization—0
APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking—0
ACR: A Benchmark for Automatic Cohort Retrieval—0
DIRAS: Efficient LLM Annotation of Document Relevance in Retrieval Augmented GenerationCode0
RE-AdaptIR: Improving Information Retrieval through Reverse Engineered Adaptation—0
Machine Learning Techniques in Automatic Music Transcription: A Systematic Survey—0
SEC-QA: A Systematic Evaluation Corpus for Financial QA—0
SciDMT: A Large-Scale Corpus for Detecting Scientific Mentions—0
CLIP-Branches: Interactive Fine-Tuning for Text-Image RetrievalCode0
Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding—0
QOG:Question and Options Generation based on Language Model—0
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval—0
A Gradient Accumulation Method for Dense Retriever under Memory Constraint—0
Iterative Utility Judgment Framework via LLMs Inspired by Relevance in Philosophy—0
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models—0
Retrieval-Augmented Feature Generation for Domain-Specific Classification—0
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels—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