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None of the 30 LLM agents evaluated in CausalGame demonstrated reliable causal thinking, revealing a critical gap in AI's ability to perform scientific reasoning.
Traditional metrics fail to capture the true memory capabilities of LLMs, exposing a critical gap in how we assess their deployment readiness.
LLMs can be guided to discover better solutions in open-ended scientific tasks by identifying and reasoning about causal factors that influence the evolutionary process.
