Fabian Probost
Biographic Data
| ID | 9634109 |
|---|---|
| NAME | Fabian Probost |
| GIVEN NAMES | Fabian |
| FAMILY NAME | Probost |
| SIGNATURE | PROBOST F |
| AFFILIATIONS | University of Hohenheim |
| ORCID | 0009-0003-2109-101X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The Crowd Without People
Large Language Models (LLMs) are transforming the innovation process by scaling ideation and creativity. This yields the challenge of evaluating the growing flood of ideas. In simpler contexts, tasks with clear criteria and well-defined outcome possibilities, where human evaluators are also a bottleneck, LLM systems are already being used as a scalable and cheap alternative. In this study, we assess whether LLMs and LLM agents can be used as eval…
Idea Evaluation for Solutions to Specialized Problems
Complex problems such as climate change pose severe challenges to societies worldwide. To overcome these challenges, digital innovation contests have emerged as a promising tool for idea generation. However, assessing idea quality in innovation contests is becoming increasingly problematic in domains where specialized knowledge is needed. Traditionally, expert juries are responsible for idea evaluation in such contests. However, experts are a sub…
No prominent works on this page.
Idea Evaluation for Solutions to Specialized Problems
Complex problems such as climate change pose severe challenges to societies worldwide. To overcome these challenges, digital innovation contests have emerged as a promising tool for idea generation. However, assessing idea quality in innovation contests is becoming increasingly problematic in domains where specialized knowledge is needed. Traditionally, expert juries are responsible for idea evaluation in such contests. However, experts are a sub…
The Crowd Without People
Large Language Models (LLMs) are transforming the innovation process by scaling ideation and creativity. This yields the challenge of evaluating the growing flood of ideas. In simpler contexts, tasks with clear criteria and well-defined outcome possibilities, where human evaluators are also a bottleneck, LLM systems are already being used as a scalable and cheap alternative. In this study, we assess whether LLMs and LLM agents can be used as eval…
Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Computational and Text Analysis Methods (1 work) · Computer Science (1 work) · Computer security (1 work) · Crowds (1 work) · Data science (1 work) · Engineering (1 work) · Ethics and Social Impacts of AI (1 work) · Human–computer interaction (1 work)