Papers Zero-shot Text Retrieval
“Zero-shot Text Retrieval” 태그가 달린 논문 7편 · 필터 해제
CLIP-PING: Boosting Lightweight Vision-Language Models with Proximus Intrinsic Neighbors Guidance
Beyond the success of Contrastive Language-Image Pre-training (CLIP), recent trends mark a shift toward exploring the applicability of lightweight vision-language models for resource-constrained scenarios. These models o…
Contrastive Learningcross-modal alignmentCross-Modal RetrievalLinear evaluation+6LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment
The video-language (VL) pretraining has achieved remarkable improvement in multiple downstream tasks. However, the current VL pretraining framework is hard to extend to multiple modalities (N modalities, N>=3) beyond vis…
Audio ClassificationContrastive LearningMultimodal Deep LearningScene Classification (unified classes)+11Keras GPT Copilot: Integrating the Power of Large Language Models in Deep Learning Model Development
Keras GPT Copilot is the first Python package designed to integrate an LLM copilot within the model development workflow, offering iterative feedback options for enhancing the performance of your Keras deep learning mode…
Data-to-Text GenerationText GenerationZero-shot Text RetrievalAltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
In this work, we present a conceptually simple and effective method to train a strong bilingual/multilingual multimodal representation model. Starting from the pre-trained multimodal representation model CLIP released by…
Contrastive LearningCross-Modal RetrievalImage ClassificationImage Retrieval+9Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese
The tremendous success of CLIP (Radford et al., 2021) has promoted the research and application of contrastive learning for vision-language pretraining. In this work, we construct a large-scale dataset of image-text pair…
Contrastive Learningimage-classificationImage ClassificationImage Retrieval+7LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval
In this paper, we propose LaPraDoR, a pretrained dual-tower dense retriever that does not require any supervised data for training. Specifically, we first present Iterative Contrastive Learning (ICoL) that iteratively tr…
Contrastive LearningRe-RankingRetrievalText Retrieval+1FLAVA: A Foundational Language And Vision Alignment Model
State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally, such models are often either cross-modal…
Image RetrievalImage-to-Text RetrievalVisual ReasoningZero-shot Image Retrieval+2