Text Matching

64 papers with code • 0 benchmarks • 6 datasets

Matching a target text to a source text based on their meaning.

Most implemented papers

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

taoxugit/AttnGAN 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

NTMC-Community/MatchZoo 20 Feb 2016

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

huggingface/transformers 10 Nov 2019

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 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

kuanghuei/SCAN ECCV 2018

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 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

cshizhe/hgr_v2t CVPR 2020

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 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 12 Aug 2019

We propose a novel framework that achieves remarkable matching performance with acceptable model complexity.

Extractive Summarization as Text Matching

maszhongming/MatchSum ACL 2020

This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems.