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. The symbolic task analysis implements the generation as an iterative procedure that scaffolds symbolic and gpt-3.5-turbo-based modules. We compare this implementation to an ablated model and a one-shot LLM-only baseline on the A3DS dataset (Tsvilodub %26 Franke%2C 2023). We find that our hybrid approach is cognitively plausible and performs well in complex contexts%2C while allowing for more open-ended modeling of language generation in a larger domain.?quality=80&w=800)
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