Papers Text Matching
“Text Matching” 태그가 달린 논문 364편 · 필터 해제
Multi-Head Attention Driven Dynamic Visual-Semantic Embedding for Enhanced Image-Text Matching
With the rapid development of multimodal learning, the image-text matching task, as a bridge connecting vision and language, has become increasingly important. Based on existing research, this study proposes an innovativ…
Image-text matchingText MatchingText RetrievalA Concept-Centric Approach to Multi-Modality Learning
In an effort to create a more efficient AI system, we introduce a new multi-modality learning framework that leverages a modality-agnostic concept space possessing abstract knowledge and a set of modality-specific projec…
Image-text matchingQuestion AnsweringText MatchingVisual Question AnsweringYou Only Submit One Image to Find the Most Suitable Generative Model
Deep generative models have achieved promising results in image generation, and various generative model hubs, e.g., Hugging Face and Civitai, have been developed that enable model developers to upload models and users t…
Image GenerationText MatchingViUniT: Visual Unit Tests for More Robust Visual Programming
Programming based approaches to reasoning tasks have substantially expanded the types of questions models can answer about visual scenes. Yet on benchmark visual reasoning data, when models answer correctly, they produce…
Image GenerationImage-text matchingQuestion AnsweringText Matching+2Vulnerability of Text-Matching in ML/AI Conference Reviewer Assignments to Collusions
In the peer review process of top-tier machine learning (ML) and artificial intelligence (AI) conferences, reviewers are assigned to papers through automated methods. These assignment algorithms consider two main factors…
Text Matchingtext similarityAutomatic Prompt Generation and Grounding Object Detection for Zero-Shot Image Anomaly Detection
Identifying defects and anomalies in industrial products is a critical quality control task. Traditional manual inspection methods are slow, subjective, and error-prone. In this work, we propose a novel zero-shot trainin…
Anomaly DetectionImage-text matchingLanguage ModelingLanguage Modelling+4VLM-HOI: Vision Language Models for Interpretable Human-Object Interaction Analysis
The Large Vision Language Model (VLM) has recently addressed remarkable progress in bridging two fundamental modalities. VLM, trained by a sufficiently large dataset, exhibits a comprehensive understanding of both visual…
Human-Object Interaction DetectionImage-text matchingLanguage ModelingLanguage Modelling+3TDSM: Triplet Diffusion for Skeleton-Text Matching in Zero-Shot Action Recognition
We firstly present a diffusion-based action recognition with zero-shot learning for skeleton inputs. In zero-shot skeleton-based action recognition, aligning skeleton features with the text features of action labels is e…
Action RecognitionSkeleton Based Action RecognitionText MatchingTriplet+3EntityCLIP: Entity-Centric Image-Text Matching via Multimodal Attentive Contrastive Learning
Recent advancements in image-text matching have been notable, yet prevailing models predominantly cater to broad queries and struggle with accommodating fine-grained query intention. In this paper, we work towards the \t…
Contrastive LearningImage-text matchingText MatchingBridging the Modality Gap: Dimension Information Alignment and Sparse Spatial Constraint for Image-Text Matching
Many contrastive learning based models have achieved advanced performance in image-text matching tasks. The key of these models lies in analyzing the correlation between image-text pairs, which involves cross-modal inter…
Contrastive LearningImage-text matchingText MatchingStoryboard guided Alignment for Fine-grained Video Action Recognition
Fine-grained video action recognition can be conceptualized as a video-text matching problem. Previous approaches often rely on global video semantics to consolidate video embeddings, which can lead to misalignment in vi…
Action RecognitionLanguage ModellingLarge Language ModelTemporal Action Localization+1Enhance Graph Alignment for Large Language Models
Graph-structured data is prevalent in the real world. Recently, due to the powerful emergent capabilities, Large Language Models (LLMs) have shown promising performance in modeling graphs. The key to effectively applying…
General KnowledgeText MatchingDISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the significant challenge of quickly and accurately pinpointing positions that align…
cognitive diagnosisContrastive LearningDisentanglementRecommendation Systems+2DARE: Diverse Visual Question Answering with Robustness Evaluation
Vision Language Models (VLMs) extend remarkable capabilities of text-only large language models and vision-only models, and are able to learn from and process multi-modal vision-text input. While modern VLMs perform well…
image-classificationImage ClassificationImage-text matchingMultiple-choice+5jina-embeddings-v3: Multilingual Embeddings With Task LoRA
We introduce jina-embeddings-v3, a novel text embedding model with 570 million parameters, achieves state-of-the-art performance on multilingual data and long-context retrieval tasks, supporting context lengths of up to …
MTEB BenchmarkRepresentation LearningRetrievalText MatchingNEVLP: Noise-Robust Framework for Efficient Vision-Language Pre-training
The success of Vision Language Models (VLMs) on various vision-language tasks heavily relies on pre-training with large scale web-crawled datasets. However, the noisy and incomplete nature of web data makes dataset scale…
Contrastive Learningcross-modal alignmentImage CaptioningImage-text matching+9LLaQo: Towards a Query-Based Coach in Expressive Music Performance Assessment
Research in music understanding has extensively explored composition-level attributes such as key, genre, and instrumentation through advanced representations, leading to cross-modal applications using large language mod…
Language ModelingLanguage ModellingText MatchingVidLPRO: A $\underline{Vid}$eo-$\underline{L}$anguage $\underline{P}$re-training Framework for $\underline{Ro}$botic and Laparoscopic Surgery
We introduce VidLPRO, a novel video-language (VL) pre-training framework designed specifically for robotic and laparoscopic surgery. While existing surgical VL models primarily rely on contrastive learning, we propose a …
Computational EfficiencyContrastive LearningLanguage ModelingLanguage Modelling+4Hound: Hunting Supervision Signals for Few and Zero Shot Node Classification on Text-attributed Graph
Text-attributed graph (TAG) is an important type of graph structured data with text descriptions for each node. Few- and zero-shot node classification on TAGs have many applications in fields such as academia and social …
NegationNode ClassificationTAGText MatchingEvaluating Attribute Comprehension in Large Vision-Language Models
Currently, large vision-language models have gained promising progress on many downstream tasks. However, they still suffer many challenges in fine-grained visual understanding tasks, such as object attribute comprehensi…
AttributeImage-text matchingQuestion AnsweringText Matching+1