Cynthia Matuszek
Biographic Data
| ID | 9079844 |
|---|---|
| NAME | Cynthia Matuszek |
| GIVEN NAMES | Cynthia |
| FAMILY NAME | Matuszek |
| SIGNATURE | MATUSZEK C |
| AFFILIATIONS | University of Maryland, Baltimore County |
| ORCID | 0000-0003-1383-8120 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Reporting Guidelines for Large Language Models in Human–Robot Interaction
The comparatively recent advent of Large Language Models (LLMs) has resulted in a wide array of new capabilities and components relevant to Human–Robot Interaction (HRI) researchers. LLMs are being applied to vision, manipulation, planning, reasoning, learning, and HRI problems, frequently as “Scarecrows,” in which LLMs serve as black box modules integrated into robot architectures for the purpose of quickly enabling full-pipeline solutions. Howe…
Scarecrows in Oz
The proliferation of Large Language Models (LLMs) presents both a critical design challenge and a remarkable opportunity for the field of Human–Robot Interaction (HRI). While the direct deployment of LLMs on interactive robots may be unsuitable for reasons of ethics, safety, and control, LLMs might nevertheless provide a promising baseline technique for many elements of HRI. Specifically, in this article, we argue for the use of LLMs as Scarecrow…
No prominent works on this page.
Scarecrows in Oz
The proliferation of Large Language Models (LLMs) presents both a critical design challenge and a remarkable opportunity for the field of Human–Robot Interaction (HRI). While the direct deployment of LLMs on interactive robots may be unsuitable for reasons of ethics, safety, and control, LLMs might nevertheless provide a promising baseline technique for many elements of HRI. Specifically, in this article, we argue for the use of LLMs as Scarecrow…
Reporting Guidelines for Large Language Models in Human–Robot Interaction
The comparatively recent advent of Large Language Models (LLMs) has resulted in a wide array of new capabilities and components relevant to Human–Robot Interaction (HRI) researchers. LLMs are being applied to vision, manipulation, planning, reasoning, learning, and HRI problems, frequently as “Scarecrows,” in which LLMs serve as black box modules integrated into robot architectures for the purpose of quickly enabling full-pipeline solutions. Howe…
Human–robot interaction (2 works) · Multimodal Machine Learning Applications (2 works) · Robot (2 works) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Computer Science (1 work) · Dissemination (1 work) · Ethics and Social Impacts of AI (1 work) · Human–computer interaction (1 work) · Information model (1 work)