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MEMPROBE is the first benchmark to study memory recovery directly, reconstructing the user state a system retains and scoring it against ground truth, and is seen as a step toward an environment where agents are trained to remember their users, growing more faithful the longer they know them.
This work introduces PrimeScientist, which jointly determines research direction and resource investment across successive research attempts, and proposes an adaptive MCTS-based allocation policy that balances exploration and exploitation using experimental feedback and remaining resources.
This work proposes a generational genetic algorithm to coordinate specialized large language model agents that integrate mechanistic arguments, reconsider assumptions, and assess evidence and testability that advances a vision of autonomous science in which AI research teams achieve a capacity for discovery beyond that...
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