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Found 3 papers, 2 papers with code
Language Agnostic Code Embeddings
Recently, code language models have achieved notable advancements in addressing a diverse array of essential code comprehension and generation tasks.
Locally Differentially Private Document Generation Using Zero Shot Prompting
Numerous studies have highlighted the privacy risks associated with pretrained large language models.
Uncovering the Hidden Cost of Model Compression
This empirical investigation underscores the need for a nuanced understanding beyond mere accuracy in sparse and quantized settings, thereby paving the way for further exploration in Visual Prompting techniques tailored for sparse and quantized models.
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