Author

Huu Tan Mai

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#artificial intelligence Preprint Sep 2026

Scalable GNN-based Knowledge Graph Representation Learning with Efficient Message Passing

This work extends Relational Sparse Matrix Multiplication (RSPMM), originally designed to losslessly lower the space complexity of composition-based MP with pointwise composition functions, to support more expressive functions (e.g., 2x2 block-diagonal matrix multiplication, Givens rotation, circular correlation).

Huu Tan Mai, Cuong Xuan Chu, Heiko Paulheim et al. · 0 citations

#artificial intelligence Preprint Sep 2026

APOLO: Automatic Prompt Optimization for Ontology Learning

This work casts OL as an explicit prompt optimization problem over LLM modules, and proposes two ontology learner architectures: a greedy and an autoregressive learner, and optimize both using GEPA, a greedy evolutionary prompt optimizer built on DSPy.

Huu Tan Mai, Roman Kochnev, Cuong Xuan Chu et al. · 0 citations