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Found 3 papers, 2 papers with code
Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination
Our results demonstrate the usefulness of this approach across different models and sizes, and also with parameter-efficient fine-tuning, offering a novel pathway to addressing the challenges with private and sensitive data in LLM applications.
CoRRPUS: Code-based Structured Prompting for Neurosymbolic Story Understanding
In this work, we capitalize on state-of-the-art Code-LLMs, such as Codex, to bootstrap the use of symbolic methods for tracking the state of stories and aiding in story understanding.
Informative Text Generation from Knowledge Triples
As the development of the encoder-decoder architecture, researchers are able to study the text generation tasks with broader types of data.
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