Can AI Agents Rebuild Machine Learning Articles? RECLAIM Benchmark Response

While the potential of artificial intelligence agents is becoming more open every day, academicians wonder how effective these systems can perform scientific research processes. RECLAIM is an innovative benchmark project designed to find the answer to this question and the machine learning is applied on 100 articles of NeurIPS 2025, one of the most prestigious conferences of the society.

The project faces a big challenge as AI agents can do:

• From software installation to debugging, all the steps required to regenerate the articles are fully automated Tags
• Identify in advance what it means to succeed for each article and identify the GPU clock budget
• Agents had to repeat results only on the basis of paper and methodology Tags
• Creating a system updated on the year basis, so it is possible to add materials from new conferences

The purpose of RECLAIM is to reveal the AI agents with concrete data, which is how competent in the actual research workflow. This benchmark contains a lot of cognitive tasks from software architecture to experiment management. The results will show where the gap between agents and human researchers is located and will determine the areas where future improvements need to focus.

The technology community sees such benchmarks as an indicator of scientific progress. RECLAIM is an important step to understand that not only today’s capabilities, but also what can come in a few years.