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Department of Electrical and Microelectronic Engineering, Kate Gleason College of Engineering, Rochester Institute of Technology
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LLMs can reliably assess social attraction but tend to exaggerate their judgments compared to human evaluators.
LLM-powered robots misinterpret comfort and strangeness in human-robot interactions, conflating engagement with comfort in their self-assessments.
VINA provides the first theoretical guarantees for INNs and NFs under realistic assumptions, finally bridging the gap between theory and practice for these powerful generative models.