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%2C TaskGen uses StrictJSON that ensures JSON output from the Large Language Model (LLM)%2C along with additional features such as type checking and iterative error correction. Key to the philosophy of TaskGen is the management of information%2Fmemory on a need-to-know basis. We empirically evaluate TaskGen on various environments such as 40x40 dynamic maze navigation with changing obstacle locations (100%25 solve rate)%2C TextWorld escape room solving with dense rewards and detailed goals (96%25 solve rate)%2C web browsing (69%25 of actions successful)%2C solving the MATH dataset (71%25 solve rate over 100 Level-5 problems)%2C Retrieval Augmented Generation on NaturalQuestions dataset (F1 score of 47.03%25)?quality=80&w=800)
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