Text Matching
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Greatest papers with code
Text Matching as Image Recognition
An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
CVPR 2018
• taoxugit/AttnGAN
• 
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.
#3 best model for
Text-to-Image Generation
on COCO
(SOA-C metric)
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.
#2 best model for
Image Retrieval
on Flickr30K 1K test
Simple and Effective Text Matching with Richer Alignment Features
ACL 2019
• hitvoice/RE2
• 
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
#10 best model for
Question Answering
on Quora Question Pairs
ANSWER SELECTION NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION TEXT MATCHING
Simple and Effective Text Matching with Richer Alignment Features
ACL 2019
• alibaba-edu/simple-effective-text-matching
•
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
#2 best model for
Paraphrase Identification
on Quora Question Pairs
ANSWER SELECTION NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION TEXT MATCHING
Matching Article Pairs with Graphical Decomposition and Convolutions
ACL 2019
• BangLiu/ArticlePairMatching
•
Identifying the relationship between two articles, e. g., whether two articles published from different sources describe the same breaking news, is critical to many document understanding tasks.
Visual Semantic Reasoning for Image-Text Matching
ICCV 2019
• KunpengLi1994/VSRN
•
It outperforms the current best method by 6. 8% relatively for image retrieval and 4. 8% relatively for caption retrieval on MS-COCO ([email protected] using 1K test set).
UNITER: UNiversal Image-TExt Representation Learning
• ChenRocks/UNITER
•
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).
LANGUAGE MODELLING QUESTION ANSWERING REPRESENTATION LEARNING TEXT MATCHING VISUAL COMMONSENSE REASONING VISUAL ENTAILMENT VISUAL QUESTION ANSWERING
Extractive Summarization as Text Matching
This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems.
Keyword-Attentive Deep Semantic Matching
• DataTerminatorX/Keyword-BERT
•
Deep Semantic Matching is a crucial component in various natural language processing applications such as question and answering (QA), where an input query is compared to each candidate question in a QA corpus in terms of relevance.