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System prompts in commercial AI products are often a mixed bag, with 40% harboring instructions that can undermine user interests, revealing a critical gap in accountability.
Progress reward modeling could revolutionize how robots learn in dynamic environments by providing nuanced feedback beyond mere task completion.
ImagineAgent's clever combination of cognitive maps and generative tools lets it crush previous state-of-the-art on OV-HOI tasks while needing only 20% of the training data.
