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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 651–671 of 671 papers

TitleStatusHype
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning—0
Understanding and Predicting Characteristics of Test Collections in Information Retrieval—0
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning—0
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training—0
Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval—0
Unifying Multimodal Retrieval via Document Screenshot Embedding—0
Uni-Mlip: Unified Self-supervision for Medical Vision Language Pre-training—0
UNITER: Learning UNiversal Image-TExt Representations—0
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation—0
V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts—0
V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts—0
Variance-Aware Loss Scheduling for Multimodal Alignment in Low-Data Settings—0
Video Editing for Video Retrieval—0
ViLEM: Visual-Language Error Modeling for Image-Text Retrieval—0
ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation—0
VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending—0
VL-BEiT: Generative Vision-Language Pretraining—0
VLMAE: Vision-Language Masked Autoencoder—0
VL-Match: Enhancing Vision-Language Pretraining with Token-Level and Instance-Level Matching—0
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