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AI as a research partner: Advancing theoretical computer science with AlphaEvolve

Google DeepMind researchers announce a paper demonstrating how AlphaEvolve, an LLM-based coding agent, discovered new combinatorial structures that improve inapproximability bounds for the MAX-4-CUT problem and tighten bounds on average-case hardness of certifying random graph properties.

From the source

In our recent paper, “Reinforced Generation of Combinatorial Structures: Applications to Complexity Theory”, we demonstrate how an LLM-powered coding agent can help discover new mathematical structures that push the boundaries of our understanding of complexity theory (a sub-field of theoretical computer science).

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Announced

30 Sep 2025 16:57 UTC