A 1.5-billion-parameter local LLM fine-tuned on generated PDDL problems achieves 66.1% single-domain and 70.6% multi-domain valid-plan rates, showing lightweight neurosymbolic planners are feasible.
Data in Brief22, 119–117 (2019)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Achieving Scalable Robot Autonomy via neurosymbolic planning using lightweight local LLM
A 1.5-billion-parameter local LLM fine-tuned on generated PDDL problems achieves 66.1% single-domain and 70.6% multi-domain valid-plan rates, showing lightweight neurosymbolic planners are feasible.