Nick DePalma
Biographic Data
| ID | 5132674 |
|---|---|
| NAME | Nick DePalma |
| GIVEN NAMES | Nick |
| FAMILY NAME | DePalma |
| SIGNATURE | DEPALMA N |
| AFFILIATIONS | Los Angeles Community College District |
| ORCID | 0000-0003-0531-743X |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| 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…
Face2Gesture
In this work, we present a method for personalizing human-robot interaction by using emotive facial expressions to generate affective robot movements. Movement is an important medium for robots to communicate affective states, but the expertise and time required to craft new robot movements promotes a reliance on fixed preprogrammed behaviors. Enabling robots to respond to multimodal user input with newly generated movements could stave off stale…
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…
Face2Gesture
In this work, we present a method for personalizing human-robot interaction by using emotive facial expressions to generate affective robot movements. Movement is an important medium for robots to communicate affective states, but the expertise and time required to craft new robot movements promotes a reliance on fixed preprogrammed behaviors. Enabling robots to respond to multimodal user input with newly generated movements could stave off stale…
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 (3 works) · Robot (3 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Human–computer interaction (2 works) · Multimodal Machine Learning Applications (2 works) · Social Robot Interaction and HRI (2 works) · Artificial Intelligence in Healthcare and Education (1 work) · Artificial neural network (1 work) · Autoencoder (1 work)