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Found 3 papers, 1 papers with code
Detecting Natural Language Biases with Prompt-based Learning
In this project, we want to explore the newly emerging field of prompt engineering and apply it to the downstream task of detecting LM biases.
CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models
Large pre-trained language models (LLMs) have been shown to have significant potential in few-shot learning across various fields, even with minimal training data.
ASSET: Autoregressive Semantic Scene Editing with Transformers at High Resolutions
We present ASSET, a neural architecture for automatically modifying an input high-resolution image according to a user's edits on its semantic segmentation map.
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