Large language models (LLMs) often fail in planning when essential preconditions are not specified. They tend to generate non-existent facts or plans that violate hard constraints.
SQ-BCP: A New Approach
Self-Querying Bidirectional Categorical Planning (SQ-BCP) has been introduced. This method explicitly represents the status of preconditions (Sat/Viol/Unk) and resolves unknowns via:
- Targeted queries to the user.
- Bridging hypotheses that establish the missing condition through an additional action.
SQ-BCP performs bidirectional search and uses a pullback-based verifier as a categorical certificate of goal compatibility, using distance-based scores only for ranking and pruning.
Results
Across WikiHow and RecipeNLG tasks with withheld preconditions, SQ-BCP reduced resource-violation rates to 14.9% and 5.8%, compared to 26.0% and 15.7% for the best baseline.
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