3 papers
cs.AI2026
When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
Mayukh Debnath, Adeyinka Adedigba, Rammohan Mallipeddi
Large language models (LLMs) struggle with classical planning, but benchmarks rarely distinguish structural difficulty from the difficulty of interpreting symbolic vocabulary. We e…
cs.RO2025
Structural Induced Exploration for Balanced and Scalable Multi-Robot Path Planning
Zikun Guo, Adeyinka P. Adedigba, Rammohan Mallipeddi +1
Multi-robot path planning is a fundamental yet challenging problem due to its combinatorial complexity and the need to balance global efficiency with fair task allocation among rob…
cs.LG2025
Cluster Aggregated GAN (CAG): A Cluster-Based Hybrid Model for Appliance Pattern Generation
Zikun Guo, Adeyinka. P. Adedigba, Rammohan Mallipeddi
Synthetic appliance data are essential for developing non-intrusive load monitoring algorithms and enabling privacy preserving energy research, yet the scarcity of labeled datasets…