SOTAVerified

Text Matching

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 364 papers

TitleStatusHype
Finding Every Medical Terms by Life Science Dictionary for MedNLP—0
Constructing Multilingual Visual-Text Datasets Revealing Visual Multilingual Ability of Vision Language Models—0
A Concept-Centric Approach to Multi-Modality Learning—0
Expressing Objects just like Words: Recurrent Visual Embedding for Image-Text Matching—0
Lattice-based lightly-supervised acoustic model training—0
Are LLMs Effective Backbones for Fine-tuning? An Experimental Investigation of Supervised LLMs on Chinese Short Text Matching—0
Enriching Conversation Context in Retrieval-based Chatbots—0
Knowledge Enhanced Hybrid Neural Network for Text Matching—0
COM3D: Leveraging Cross-View Correspondence and Cross-Modal Mining for 3D Retrieval—0
Enhanced Sentence Alignment Network for Efficient Short Text Matching—0
Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse—0
Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators—0
Embedding Arithmetic of Multimodal Queries for Image Retrieval—0
Enhance Graph Alignment for Large Language Models—0
Efficient Media Retrieval from Non-Cooperative Queries—0
EntityCLIP: Entity-Centric Image-Text Matching via Multimodal Attentive Contrastive Learning—0
A Self-Boosting Framework for Automated Radiographic Report Generation—0
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE—0
Dynamic and Compressive Adaptation of Transformers From Images to Videos—0
CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models—0
Advanced Multimodal Deep Learning Architecture for Image-Text Matching—0
FASTMATCH: Accelerating the Inference of BERT-based Text Matching—0
Dual Embodied-Symbolic Concept Representations for Deep Learning—0
A Novel Attention-based Aggregation Function to Combine Vision and Language—0
K-AID: Enhancing Pre-trained Language Models with Domain Knowledge for Question Answering—0
DT2I: Dense Text-to-Image Generation from Region Descriptions—0
ClusterFormer: Neural Clustering Attention for Efficient and Effective Transformer—0
Don't Stop Learning: Towards Continual Learning for the CLIP Model—0
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots—0
CLIP-Powered TASS: Target-Aware Single-Stream Network for Audio-Visual Question Answering—0
A Multi-Perspective Architecture for Semantic Code Search—0
Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching—0
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching—0
jina-embeddings-v3: Multilingual Embeddings With Task LoRA—0
Knowledge Aware Semantic Concept Expansion for Image-Text Matching—0
Learning Comprehensive Representations with Richer Self for Text-to-Image Person Re-Identification—0
DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling—0
A Measurement-Based Quantum-Like Language Model for Text Matching—0
Descriptive Image-Text Matching with Graded Contextual Similarity—0
CLIP4Caption: CLIP for Video Caption—0
Adaptive Feature Discrimination and Denoising for Asymmetric Text Matching—0
Dependency Structure Augmented Contextual Scoping Framework for Multimodal Aspect-Based Sentiment Analysis—0
Characterizing drug mentions in COVID-19 Twitter Chatter—0
DEMO: A Statistical Perspective for Efficient Image-Text Matching—0
CGI: Identifying Conditional Generative Models with Example Images—0
Biomedical Evidence Generation Engine—0
Deep Neural Review Text Interaction for Recommendation Systems—0
BURT: BERT-inspired Universal Representation from Learning Meaningful Segment—0
Deep Learning for Biomedical Information Retrieval: Learning Textual Relevance from Click Logs—0
Deep Learning Applied to Image and Text Matching—0
Show:102550
← PrevPage 3 of 8Next →

No leaderboard results yet.