Mar 20, 2024 · In this paper, we propose the CodePLAN framework, which aims to transfer LLMs' reasoning capabilities to smaller models through distillation.
Mar 20, 2024 · In this paper, we propose the CodePLAN framework, which aims to transfer LLMs' reasoning capabilities to smaller models through distillation.
May 20, 2024 · In this paper, we propose the. CodePLAN framework, which aims to transfer LLMs' reasoning capabilities to smaller models through distillation.
Consequently, there arises a compelling need for transferring LLMs' code generation reasoning abilities to the smaller models. In this paper, we propose the ...
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[PDF] Distilling Complex Reasoning Capabilities from LLMs by ...
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Thus, the goal of our research is to enable complex arithmetic reasoning in small models for deploying at scale. Knowledge distillation (Hinton, Vinyals, and ...
Discover how the CodePLAN framework leverages the reasoning capabilities of LLMs to boost the code generation performance of smaller models by over 130% on ...
The CodePLAN framework seeks to distill LLMs' reasoning prowess into smaller models using a multi-task learning approach focusing on both code and solution plan ...
Apr 11, 2024 · In this work, we propose a novel approach to distilling reasoning abilities from LLMs by leveraging their capacity to explain solutions. We ...
Smaller models can be trained on LLMs' data to improve their performance, which can further serve as cost-effective alternatives to LLMs for the given task ( ...
Feb 20, 2024 · This survey delves into knowledge distillation (KD) techniques in Large Language Models (LLMs), highlighting KD's crucial role in transferring advanced ...