Zero-shot Text Retrieval
6 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Zero-shot Text Retrieval
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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Flickr30k-CNA
WebLI
Most implemented papers
LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment
pku-yuangroup/languagebind
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We thus propose VIDAL-10M with Video, Infrared, Depth, Audio and their corresponding Language, naming as VIDAL-10M.
FLAVA: A Foundational Language And Vision Alignment Model
facebookresearch/multimodal
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CVPR 2022
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.
LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval
jetrunner/laprador
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Findings (ACL) 2022
Experimental results show that LaPraDoR achieves state-of-the-art performance compared with supervised dense retrieval models, and further analysis reveals the effectiveness of our training strategy and objectives.
Chinese 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.
AltCLIP: 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.
Keras GPT Copilot: Integrating the Power of Large Language Models in Deep Learning Model Development
fabprezja/keras-gpt-copilot
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Zenodo GitHub 2023
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 models.
