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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

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Showing 281–290 of 671 papers

TitleStatusHype
Establishing a Foundation for Tetun Ad-Hoc Text Retrieval: Stemming, Indexing, Retrieval, and Ranking—0
CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR—0
Adversarial Retriever-Ranker for dense text retrieval—0
ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling—0
Knowledge Transfer Across Modalities with Natural Language Supervision—0
Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG—0
jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images—0
Enhancing Knowledge Retrieval with In-Context Learning and Semantic Search through Generative AI—0
Arabic Text Mining—0
End-to-End Autoregressive Retrieval via Bootstrapping for Smart Reply Systems—0
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