Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929358521761792 |
|---|---|
| author | Jensen, Emily Sankaranarayanan, Sriram Hayes, Bradley |
| author_facet | Jensen, Emily Sankaranarayanan, Sriram Hayes, Bradley |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_16344 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks Jensen, Emily Sankaranarayanan, Sriram Hayes, Bradley Robotics 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. |
| title | Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks |
| topic | Robotics |
| url | https://arxiv.org/abs/2405.16344 |