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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 326–350 of 671 papers

TitleStatusHype
Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language RepresentationsCode1
h2oGPT: Democratizing Large Language ModelsCode6
Global and Local Semantic Completion Learning for Vision-Language Pre-trainingCode1
Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New BenchmarkCode1
Revisiting the Role of Language Priors in Vision-Language ModelsCode1
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language ModelsCode1
FuseCap: Leveraging Large Language Models for Enriched Fused Image CaptionsCode1
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language TransformersCode1
Integrating Listwise Ranking into Pairwise-based Image-Text RetrievalCode0
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest NeighborsCode0
PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional ExpertsCode0
S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist CaptionsCode1
When the Music Stops: Tip-of-the-Tongue Retrieval for MusicCode0
i-Code Studio: A Configurable and Composable Framework for Integrative AI—0
VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending—0
Enhancing Vision-Language Pre-Training with Jointly Learned Questioner and Dense CaptionerCode1
TOME: A Two-stage Approach for Model-based Retrieval—0
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
Mask to reconstruct: Cooperative Semantics Completion for Video-text Retrieval—0
Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision TransformersCode1
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception—0
Cross-Modal Retrieval for Motion and Text via DopTriple LossCode1
Understanding Differential Search Index for Text RetrievalCode1
From Association to Generation: Text-only Captioning by Unsupervised Cross-modal MappingCode1
Hypernymization of named entity-rich captions for grounding-based multi-modal pretraining—0
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