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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 401–450 of 671 papers

TitleStatusHype
LuoJiaHOG: A Hierarchy Oriented Geo-aware Image Caption Dataset for Remote Sensing Image-Text Retrival—0
Multiscale Matching Driven by Cross-Modal Similarity Consistency for Audio-Text Retrieval—0
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?—0
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval—0
Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings—0
MORE: Multi-mOdal REtrieval Augmented Generative Commonsense Reasoning—0
PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods—0
Multimodal Learned Sparse Retrieval for Image Suggestion—0
Video Editing for Video Retrieval—0
Embracing Language Inclusivity and Diversity in CLIP through Continual Language LearningCode0
Enhancing Image-Text Matching with Adaptive Feature AggregationCode0
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment—0
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving—0
Building Vision-Language Models on Solid Foundations with Masked Distillation—0
OTE: Exploring Accurate Scene Text Recognition Using One TokenCode0
Accept the Modality Gap: An Exploration in the Hyperbolic Space—0
Filter & Align: Leveraging Human Knowledge to Curate Image-Text Data—0
Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning—0
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models—0
LightCLIP: Learning Multi-Level Interaction for Lightweight Vision-Language Models—0
IG Captioner: Information Gain Captioners are Strong Zero-shot Classifiers—0
Invisible Relevance Bias: Text-Image Retrieval Models Prefer AI-Generated ImagesCode0
Towards Robust Text Retrieval with Progressive LearningCode0
Text Retrieval with Multi-Stage Re-Ranking ModelsCode0
Noisy Pair Corrector for Dense Retrieval—0
A New Fine-grained Alignment Method for Image-text Matching—0
FLAP: Fast Language-Audio Pre-training—0
Harvest Video Foundation Models via Efficient Post-Pretraining—0
MCAD: Multi-teacher Cross-modal Alignment Distillation for efficient image-text retrieval—0
End-to-End Autoregressive Retrieval via Bootstrapping for Smart Reply Systems—0
SILC: Improving Vision Language Pretraining with Self-Distillation—0
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning—0
On Using GUI Interaction Data to Improve Text Retrieval-based Bug LocalizationCode0
Direction-Oriented Visual-semantic Embedding Model for Remote Sensing Image-text Retrieval—0
Policy-Gradient Training of Language Models for Ranking—0
Constructing Image-Text Pair Dataset from Books—0
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal AnalysisCode0
Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval—0
Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval—0
Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense RetrievalCode0
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking—0
Dual Relation Alignment for Composed Image Retrieval—0
MultiWay-Adapater: Adapting large-scale multi-modal models for scalable image-text retrievalCode0
Contrastive Feature Masking Open-Vocabulary Vision Transformer—0
Killing two birds with one stone: Can an audio captioning system also be used for audio-text retrieval?—0
DLIP: Distilling Language-Image Pre-training—0
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE—0
Hybrid Retrieval and Multi-stage Text Ranking Solution at TREC 2022 Deep Learning Track—0
Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks—0
Embedding-based Retrieval with LLM for Effective Agriculture Information Extracting from Unstructured Data—0
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