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New York University, Abu Dhabi
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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.
Achieving full-stack fidelity in live simulations without sacrificing performance could revolutionize how we evaluate distributed systems before deployment.
Cordon reveals that a transactional approach to LLM agent runtimes can drastically reduce irreversible failures while enhancing task integrity across complex workflows.
Turns out, the best way to get an LLM to generate good text-to-image prompts is to have it mimic existing images, not plan from scratch.
