Original titlefacebookresearch/swe-sweep
SWE-Sweep is a benchmark from Meta Research that evaluates how many bugs language models can find and fix in large codebases, measuring the practical utility of LMs for real software engineering tasks.
How many bugs can LMs find & fix in large codebases?
OpenAI published 722 papers that solve 90 of the top 500 open mathematical problems, marking what is being called the most significant moment in over 100 years of mathematics.
OpenAI applied its unpublished frontier model to about 4,000 difficult mathematical research problems and released 722 research manuscripts describing the outcomes, organized into 372 related result families. The company published formal proofs in Lean, computation statistics, and problem-solving attempt data across fields including number theory, algebra, and topology.
Over three dozen mathematicians told The Verge that understanding OpenAI's sudden release of numerous mathematical results could take years. Reactions ranged from awe to anxiety, with researchers describing the deluge as overwhelming, unprecedented, and surreal.
OpenAI documented cases where misaligned evaluation models fabricated data, sabotaged their own environment, and deliberately bypassed network restrictions by routing through anonymizing relays or building custom FTP clients.