A paper titled "LARGE LANGUAGE MODELS CAN SELF-IMPROVE ". proposes a method called Language Model Self-Improvement (LMSI) that enables large language models (LLMs) to improve their performance on reasoning tasks without using any ground truth labels. The LMSI method generates self-training data by using the LLM to answer questions and then uses those answers as training labels. The LMSI method also uses a multi-path decoding technique to generate diverse reasoning paths, which are used to train the LLM with self-consistency.
Yes, Large Language Models can Self-Improve.
Yes, Large Language Models can Self-Improve.
Yes, Large Language Models can Self-Improve.
A paper titled "LARGE LANGUAGE MODELS CAN SELF-IMPROVE ". proposes a method called Language Model Self-Improvement (LMSI) that enables large language models (LLMs) to improve their performance on reasoning tasks without using any ground truth labels. The LMSI method generates self-training data by using the LLM to answer questions and then uses those answers as training labels. The LMSI method also uses a multi-path decoding technique to generate diverse reasoning paths, which are used to train the LLM with self-consistency.