Author

A. Adedigba

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#artificial intelligence Preprint Oct 2026

When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability

Improved hybrid planning requires modeling LLM behavior sensitive to predicate semantics rather than developing more structural predictors, and progressively rename predicates while preserving states, transitions, and optimal plans in STRIPS domains with BFS-optimal plan lengths.

Mayukh Debnath, A. Adedigba, Rammohan Mallipeddi · 0 citations

#artificial intelligence Dec 2025

Cluster Aggregated GAN (CAG): A Cluster-Based Hybrid Model for Appliance Pattern Generation

The proposed Cluster Aggregated GAN framework is established, a hybrid generative approach that routes each appliance to a specialized branch based on its behavioral characteristics that consistently outperforms baseline methods across metrics measuring realism, diversity, and training stability.

Zikun Guo, A. Adedigba, Rammohan Mallipeddi · arXiv.org · 1 citation