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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 376–400 of 671 papers

TitleStatusHype
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP—0
Balancing Reinforcement Learning Training Experiences in Interactive Information Retrieval—0
Barking Up The Syntactic Tree: Enhancing VLM Training with Syntactic Losses—0
Beat: Bi-directional One-to-Many Embedding Alignment for Text-based Person Retrieval—0
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving—0
Beyond Coarse-Grained Matching in Video-Text Retrieval—0
Beyond Cropped Regions: New Benchmark and Corresponding Baseline for Chinese Scene Text Retrieval in Diverse Layouts—0
BIOSSES: A Semantic Sentence Similarity Estimation System for the Biomedical Domain—0
BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?—0
Boosting Video-Text Retrieval with Explicit High-Level Semantics—0
Breaking Language Barriers or Reinforcing Bias? A Study of Gender and Racial Disparities in Multilingual Contrastive Vision Language Models—0
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs—0
Bridging Classical and Quantum String Matching: A Computational Reformulation of Bit-Parallelism—0
Bridging Queries and Tables through Entities in Table Retrieval—0
Building Vision-Language Models on Solid Foundations with Masked Distillation—0
Can BERT Dig It? -- Named Entity Recognition for Information Retrieval in the Archaeology Domain—0
C-DLSI: An Extended LSI Tailored for Federated Text Retrieval—0
CEIA: CLIP-Based Event-Image Alignment for Open-World Event-Based Understanding—0
CiCo: Domain-Aware Sign Language Retrieval via Cross-Lingual Contrastive Learning—0
CLIP2TV: Align, Match and Distill for Video-Text Retrieval—0
CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR—0
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?—0
CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval—0
CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval—0
CoLLAP: Contrastive Long-form Language-Audio Pretraining with Musical Temporal Structure Augmentation—0
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