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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 451–500 of 671 papers

TitleStatusHype
NEVLP: Noise-Robust Framework for Efficient Vision-Language Pre-training—0
NLIP: Noise-robust Language-Image Pre-training—0
Benchmarking and Building Zero-Shot Hindi Retrieval Model with Hindi-BEIR and NLLB-E5—0
Noisy Pair Corrector for Dense Retrieval—0
NOMAD: Linguistic Resources and Tools Aimed at Policy Formulation and Validation—0
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks—0
On Negative Sampling for Contrastive Audio-Text Retrieval—0
On Reducing the Number of Visual Words in the Bag-of-Features Representation—0
On the Equilibrium of Query Reformulation and Document Retrieval—0
On-the-fly Text Retrieval for End-to-End ASR Adaptation—0
On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures—0
On the Value of Behavioral Representations for Dense Retrieval—0
Optimizing Multi-Stage Language Models for Effective Text Retrieval—0
Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval—0
Pairing Clustered Inverted Indexes with kNN Graphs for Fast Approximate Retrieval over Learned Sparse Representations—0
PathAlign: A vision-language model for whole slide images in histopathology—0
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models—0
Personalized Text Retrieval for Learners of Chinese as a Foreign Language—0
PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods—0
Playing Lottery Tickets with Vision and Language—0
Policy-Gradient Training of Language Models for Ranking—0
Retrieval-based Disentangled Representation Learning with Natural Language Supervision—0
RETTA: Retrieval-Enhanced Test-Time Adaptation for Zero-Shot Video Captioning—0
Revising Image-Text Retrieval via Multi-Modal Entailment—0
Robotic Environmental State Recognition with Pre-Trained Vision-Language Models and Black-Box Optimization—0
Robotic State Recognition with Image-to-Text Retrieval Task of Pre-Trained Vision-Language Model and Black-Box Optimization—0
Robust Cross-Modal Representation Learning with Progressive Self-Distillation—0
RSVG: Exploring Data and Models for Visual Grounding on Remote Sensing Data—0
Scale-Semantic Joint Decoupling Network for Image-text Retrieval in Remote Sensing—0
Scene Graph Based Fusion Network For Image-Text Retrieval—0
Scene-Text Aware Image and Text Retrieval with Dual-Encoder—0
Scientometric Analysis of the German IR Community within TREC & CLEF—0
Searching Four-Millenia-Old Digitized Documents: A Text Retrieval System for Egyptologists—0
Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement—0
SeLIP: Similarity Enhanced Contrastive Language Image Pretraining for Multi-modal Head MRI—0
Semantic Indexing of Multilingual Corpora and its Application on the History Domain—0
Semantic Search by Latent Ontological Features—0
SemCORE: A Semantic-Enhanced Generative Cross-Modal Retrieval Framework with MLLMs—0
Show, Recall, and Tell: Image Captioning with Recall Mechanism—0
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features—0
SILC: Improving Vision Language Pretraining with Self-Distillation—0
SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval—0
SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval—0
SparTerm: Learning Term-based Sparse Representation for Fast Text Retrieval—0
SPECTRUM: Semantic Processing and Emotion-informed video-Captioning Through Retrieval and Understanding Modalities—0
Spotify at TREC 2020: Genre-Aware Abstractive Podcast Summarization—0
Stacked Convolutional Deep Encoding Network for Video-Text Retrieval—0
STAIR: Learning Sparse Text and Image Representation in Grounded Tokens—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval—0
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