Jul 16, 2024 · Zero-shot learning is a technique that enables pre-trained models to predict class labels of previously unknown data, i.e., data samples not present in the ...

Jul 3, 2024 · In this paper, we propose reverse inference optimization (RIO), a simple and effective method designed to enhance the robustness of autoregressive-model-based ...

4 days ago · A: Zero-shot involves using LLMs for new tasks without prior labeled data. Few-shot employs a few labeled examples in prompts to quickly adapt models to new ...

Jul 3, 2024 · Through zero-shot inference with text prompts, ZEAL predicts segmentation masks, capturing essential features of both instruments and surroundings.

Jul 10, 2024 · During inference, the model uses these learned attributes to identify an unseen class, in this case, a zebra, by recognizing it as a horse-like animal with ...

1 day ago · Zero-shot inference is a powerful paradigm that enables the use of large pretrained models for downstream classification tasks without further training. However ...

Jul 10, 2024 · Fine-tunes the model with just 1 minute of training data to enhance voice similarity and realism. Cross-Lingual Support. Supports inference in different ...

3 days ago · We propose to exploit mid-level semantic knowledge transfer for federated learning from independent non-overlapping class label spaces and introduce a new ...

Jul 11, 2024 · This human ability to infer and recognize based on descriptions is exactly what zero-shot learning (ZSL) aims to achieve in artificial intelligence [1]. In ...

Jul 23, 2024 · The Zero Shot Detection AI service exposes REST API endpoints to control stream input and objects to detect. This wiki provides a tutorial on how to run Zero- ...