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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.
LLMs can now tackle complex TCS proof generation with a benchmark that achieves over 90% accuracy in verification against human experts.
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.