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New framework guides LLM prompting for grounded robot personas

By PulseAugur Editorial · [1 sources] ·

A new research paper proposes a framework for designing prompts for large language models (LLMs) used in social robots. The framework aims to address issues like hallucinated capabilities and unclear behavioral boundaries by providing a structured prompt template with eight functional components. This approach is intended to improve the legibility of robot personalities, allow for user adaptation, and address ethical concerns related to safety and deception in human-robot interaction. AI

IMPACT This research could lead to more predictable and trustworthy robot behavior, enhancing user trust and safety in human-robot interactions.

RANK_REASON The cluster contains a research paper detailing a new framework for LLM-based human-robot interaction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework guides LLM prompting for grounded robot personas

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The cluster contains a research paper detailing a new framework for LLM-based human-robot interaction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ashita Ashok, Franziska Babel, Patrick Holthaus, Rucha Khot, Karla Bransky, Fethiye Irmak Dogan, Karsten Berns, Silvia Rossi, Minha Lee, Guy Laban ·

    Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI

    arXiv:2608.26182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for verbal interaction in social robots, yet prompt design in human-robot interaction (HRI) remains underspecified. As a result, robots may present hallucinated capabilities, unclea…

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