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 1176–1200 of 4740 papers

TitleStatusHype
Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy—0
IM-RAG: Multi-Round Retrieval-Augmented Generation Through Learning Inner Monologues—0
Modeling User Preferences via Brain-Computer Interfacing—0
Error-margin Analysis for Hidden Neuron Activation LabelsCode0
LGDE: Local Graph-based Dictionary ExpansionCode0
Identifying Key Terms in Prompts for Relevance Evaluation with GPT Models—0
Event GDR: Event-Centric Generative Document Retrieval—0
Explaining Text Similarity in Transformer ModelsCode0
A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models—0
Redefining Information Retrieval of Structured Database via Large Language Models—0
ChatSOS: Vector Database Augmented Generative Question Answering Assistant in Safety Engineering—0
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems—0
LLMs Can Patch Up Missing Relevance Judgments in Evaluation—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
CleanGraph: Human-in-the-loop Knowledge Graph Refinement and CompletionCode0
MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering—0
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models—0
Beyond Relevance: Evaluate and Improve Retrievers on Perspective AwarenessCode0
IQLS: Framework for leveraging Metadata to enable Large Language Model based queries to complex, versatile Data—0
Semi-Parametric Retrieval via Binary Bag-of-Tokens IndexCode0
SUKHSANDESH: An Avatar Therapeutic Question Answering Platform for Sexual Education in Rural India—0
Comparative Analysis of Retrieval Systems in the Real World—0
Distillation for Multilingual Information Retrieval—0
Question Suggestion for Conversational Shopping Assistants Using Product Metadata—0
"In-Context Learning" or: How I learned to stop worrying and love "Applied Information Retrieval"—0
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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