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Optimal $O(\sqrt{d})$ regret in online inverse linear optimization is now achievable in polynomial time, shattering previous computational barriers.
Stellar Colosseum is introduced, a model-agnostic harness for allocating inference across research in mathematics and theoretical computer science that demonstrates the capabilities of Colosseum through open-ended research and evaluations on theorem-proving and competitive programming benchmarks.
SSTQ cuts communication costs in federated learning while ensuring privacy, achieving optimal mean squared error scaling with minimal bit usage.
No randomized polynomial-time algorithm can overcome the condition-number barrier in sparse least-squares optimization, confirming a long-standing conjecture.
Nearly optimal dimension lower bounds reveal that single-vector embeddings for MAX-IP require significantly more dimensions than previously thought, closing a critical gap in the literature.
An AI agent cracked an open problem in theoretical physics, deriving exact analytical solutions for gravitational radiation from cosmic strings, proving AI can do more than just pattern recognition.
Gemini 3 Deep Think can now autonomously solve a majority of problems in a challenging math competition, signaling a leap in AI's mathematical reasoning capabilities.
