Text Matching
64 papers with code • 0 benchmarks • 6 datasets
Matching a target text to a source text based on their meaning.
Benchmarks
These leaderboards are used to track progress in Text Matching
Snopes
DuLeMon
Most implemented papers
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
taoxugit/AttnGAN
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CVPR 2018
In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation.
Text Matching as Image Recognition
An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships that are derived from an external knowledge base or co-occurrence in the same article.
UNITER: UNiversal Image-TExt Representation Learning
ChenRocks/UNITER
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ECCV 2020
Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).
Stacked Cross Attention for Image-Text Matching
Prior work either simply aggregates the similarity of all possible pairs of regions and words without attending differentially to more and less important words or regions, or uses a multi-step attentional process to capture limited number of semantic alignments which is less interpretable.
Simple and Effective Text Matching with Richer Alignment Features
hitvoice/RE2
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ACL 2019
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
To improve fine-grained video-text retrieval, we propose a Hierarchical Graph Reasoning (HGR) model, which decomposes video-text matching into global-to-local levels.
Dual Attention Networks for Multimodal Reasoning and Matching
iammrhelo/pytorch-vqa-dan
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CVPR 2017
We propose Dual Attention Networks (DANs) which jointly leverage visual and textual attention mechanisms to capture fine-grained interplay between vision and language.
Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
Wangt-CN/MTFN-RR-PyTorch-Code
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We propose a novel framework that achieves remarkable matching performance with acceptable model complexity.
Extractive Summarization as Text Matching
maszhongming/MatchSum
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ACL 2020
This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems.
