Part 2/8:
The framework for this exploration is called Paperbench, which acts as a benchmark evaluating AI's ability to replicate the results of ML research papers. The focus of Paperbench is clear: allow AI agents to examine papers, write and execute corresponding code, and achieve empirical results identical to those presented in the original research.
The paper highlights the intricacies of this experimental setup. Replicating findings from academic papers involves considerable skill and effort, often requiring human experts several days to complete. With AI agents equipped with sophisticated tools—including web browsing capabilities and coding environments like bash and Python—this task can now be accomplished in mere hours.