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Text Retrieval

Text Retrieval is the task of finding the most text result (such as an answer, paragraph, or passage) given a query (which could be a question, keywords, or any relevant text)

Papers

Showing 276300 of 671 papers

TitleStatusHype
EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models0
Evaluation of Deep Gaussian Processes for Text Classification0
Evaluating D-MERIT of Partial-annotation on Information Retrieval0
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?0
Are we there yet? Exploring clinical domain knowledge of BERT models0
Establishing a Foundation for Tetun Ad-Hoc Text Retrieval: Stemming, Indexing, Retrieval, and Ranking0
CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR0
Adversarial Retriever-Ranker for dense text retrieval0
ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling0
LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning0
Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG0
Enhancing Knowledge Retrieval with In-Context Learning and Semantic Search through Generative AI0
Arabic Text Mining0
End-to-End Autoregressive Retrieval via Bootstrapping for Smart Reply Systems0
CLIP2TV: Align, Match and Distill for Video-Text Retrieval0
Label Smoothing for Text Mining0
CiCo: Domain-Aware Sign Language Retrieval via Cross-Lingual Contrastive Learning0
Embedding-based Retrieval with LLM for Effective Agriculture Information Extracting from Unstructured Data0
CEIA: CLIP-Based Event-Image Alignment for Open-World Event-Based Understanding0
Adversarial Attack on Deep Cross-Modal Hamming Retrieval0
C-DLSI: An Extended LSI Tailored for Federated Text Retrieval0
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss0
A Proposed Conceptual Framework for a Representational Approach to Information Retrieval0
Accept the Modality Gap: An Exploration in the Hyperbolic Space0
Learning to embed semantic similarity for joint image-text retrieval0
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