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Towards Autonomous Mathematics Research (arxiv.org)
u1hcw9nx 12 minutes ago [-]
>The results of this paper should not be interpreted as suggesting that AI can consistently solve research-level mathematics questions. In fact, our anecdotal experience is the opposite: success cases are rare, and an apt intuition for autonomous capabilities (and limitations) may currently be important for finding such cases. The papers (ACGKMP26; Feng26; LeeSeo26) grew out of spontaneous positive outcomes in a wider benchmarking effort on research-level problems; for most of these problems, no autonomous progress was made.
amiune 1 hours ago [-]
Perfect match for this test: https://arxiv.org/abs/2602.05192
bwfan123 40 minutes ago [-]
noosphr 20 minutes ago [-]
This is what everyone who uses llms regularly expected. Good results require a human in the loop and the internet is so big that just about everything has been done there by someone. Most often you.
1 hours ago [-]
measurablefunc 1 hours ago [-]
I still don't get how achieving 96% on some benchmark means it's a super genius but that last 4% is somehow still out of reach. The people who constantly compare robots to people should really ponder how a person who manages to achieve 90% on some advanced math benchmark still misses that last 10% somehow.
botusaurus 33 minutes ago [-]
do you think Terence Tao can solve any math problem in the world that is solvable by another matematician?
tug2024 3 minutes ago [-]
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nivcmo 1 hours ago [-]
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