Our paper won the outstanding paper award at EACL 2024!
Our paper entitled “MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks” [Zhang et al., 2024]1 was presented at the EACL 2024 conference and won the the outstanding paper award.
In this paper, we aim to bridge the gap between machine intelligence and human knowledge by introducing a novel framework, which leverages the state-of-the-art large language models to develop ML solutions for novel tasks. We showcase the possibility of extending the capability of LLMs to comprehend structured inputs and perform thorough reasoning for solving novel ML tasks. And we find that, after some dedicated design, the LLM can (i) observe from the existing experiences of ML tasks and (ii) reason effectively to deliver promising results for new tasks. The solution generated can be used directly to achieve high levels of competitiveness. Examples and code available at this https URL.