3 papers
cs.AI2025
Procedural Knowledge Improves Agentic LLM Workflows
Vincent Hsiao, Mark Roberts, Leslie Smith
Large language models (LLMs) often struggle when performing agentic tasks without substantial tool support, prom-pt engineering, or fine tuning. Despite research showing that domai…
cs.AI2025
Bootstrapping Human-Like Planning via LLMs
David Porfirio, Vincent Hsiao, Morgan Fine-Morris +2
Robot end users increasingly require accessible means of specifying tasks for robots to perform. Two common end-user programming paradigms include drag-and-drop interfaces and natu…
cs.AI2025
Automating Curriculum Learning for Reinforcement Learning using a Skill-Based Bayesian Network
Vincent Hsiao, Mark Roberts, Laura M. Hiatt +2
A major challenge for reinforcement learning is automatically generating curricula to reduce training time or improve performance in some target task. We introduce SEBNs (Skill-Env…