Large-scale analysis of wild LLM chat logs finds that user interaction patterns stabilize quickly after initial use and correlate with long-term outcomes like retention, creating an agency paradox of limited exploration in unconstrained systems.
Collins, Albert Q
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Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
Multimodal LLMs in robots develop self-identification and predictive awareness through sensorimotor loops, with structural equation modeling linking sensory integration to dimensions of the minimal self.
citing papers explorer
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Priming, Path-dependence, and Plasticity: Understanding the molding of user-LLM interaction and its implications from (many) chat logs in the wild
Large-scale analysis of wild LLM chat logs finds that user interaction patterns stabilize quickly after initial use and correlate with long-term outcomes like retention, creating an agency paradox of limited exploration in unconstrained systems.
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Results-Actionability Gap: Understanding How Practitioners Evaluate LLM Products in the Wild
Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
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Sensorimotor Self-Recognition in Multimodal Large Language Model-Driven Robots
Multimodal LLMs in robots develop self-identification and predictive awareness through sensorimotor loops, with structural equation modeling linking sensory integration to dimensions of the minimal self.