English

Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks

Robotics 2024-05-28 v1

Abstract

We claim that LLMs can be paired with formal analysis methods to provide accessible, relevant feedback for HRI tasks. While logic specifications are useful for defining and assessing a task, these representations are not easily interpreted by non-experts. Luckily, LLMs are adept at generating easy-to-understand text that explains difficult concepts. By integrating task assessment outcomes and other contextual information into an LLM prompt, we can effectively synthesize a useful set of recommendations for the learner to improve their performance.

Keywords

Cite

@article{arxiv.2405.16344,
  title  = {Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks},
  author = {Emily Jensen and Sriram Sankaranarayanan and Bradley Hayes},
  journal= {arXiv preprint arXiv:2405.16344},
  year   = {2024}
}

Comments

Presented at Human-LLM Interaction Workshop at HRI 2024

R2 v1 2026-06-28T16:40:25.995Z