Text Matching
Leaderboards
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.
SOTA for Text-to-Image Generation on CUB
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
ACL 2019
• hitvoice/RE2
• 
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
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: Learning UNiversal Image-TExt Representations
• ChenRocks/UNITER
•
Joint image-text embedding is the bedrock for most Vision-and-Language (V+L) tasks, where multimodality inputs are jointly processed for visual and textual understanding.
LANGUAGE MODELLING QUESTION ANSWERING TEXT MATCHING VISUAL COMMONSENSE REASONING VISUAL QUESTION ANSWERING
Lattice CNNs for Matching Based Chinese Question Answering
• Erutan-pku/LCN-for-Chinese-QA
•
Short text matching often faces the challenges that there are great word mismatch and expression diversity between the two texts, which would be further aggravated in languages like Chinese where there is no natural space to segment words explicitly.
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
• yangliuy/NeuralResponseRanking
•
Our models and research findings provide new insights on how to utilize external knowledge with deep neural models for response selection and have implications for the design of the next generation of information-seeking conversation systems.