Creative Problem Solving in Large Language and Vision Models -- What Would it Take?
Nair, Lakshmi, Gizzi, Evana, Sinapov, Jivko
–arXiv.org Artificial Intelligence
In Given this overview, we see that LLVMs both at the highlevel this section, we discuss how typical task planning is achieved and low-level, can be modified to incorporate creative with LLVMs. We divide the discussion into three subsections problem solving into task planning. For instance, the high-level based on the level of task planning abstraction where LLVMs task plans generated can encompass a novel substitution for a are applied: a) high-level task planning, b) low-level task missing object, whereas the low-level task plan can generate planning, and c) hybrid task planning.
arXiv.org Artificial Intelligence
May-2-2024
- Country:
- North America
- United States
- Massachusetts > Middlesex County
- Medford (0.04)
- Georgia > Fulton County
- Atlanta (0.04)
- Massachusetts > Middlesex County
- Canada > Quebec
- Capitale-Nationale Region
- Québec (0.04)
- Quebec City (0.04)
- Capitale-Nationale Region
- United States
- North America
- Genre:
- Research Report (1.00)
- Industry:
- Health & Medicine (0.68)
- Technology:
- Information Technology > Artificial Intelligence
- Vision (1.00)
- Robots (1.00)
- Natural Language > Large Language Model (1.00)
- Cognitive Science (1.00)
- Machine Learning > Neural Networks
- Deep Learning (0.47)
- Information Technology > Artificial Intelligence