Text Matching
159 papers with code • 0 benchmarks • 7 datasets
Matching a target text to a source text based on their meaning.
Benchmarks
These leaderboards are used to track progress in Text Matching
Most implemented papers
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
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.
UNITER: UNiversal Image-TExt Representation Learning
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).
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.
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.
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.
ColPali: Efficient Document Retrieval with Vision Language Models
Documents are visually rich structures that convey information through text, but also figures, page layouts, tables, or even fonts.
Simple and Effective Text Matching with Richer Alignment Features
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
To these ends, we propose a simpler but more effective Deep Fusion Generative Adversarial Networks (DF-GAN).
Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations
In this paper, we present an end-to-end framework Structure-CLIP, which integrates Scene Graph Knowledge (SGK) to enhance multi-modal structured representations.