Ming-Qiao Mo

Though Language Models Err While They Strive: Conformal Prediction for Self-Correcting Scientific Generation

Scientific Feasibility Control SFC is introduced, a graph-structured conformal prediction framework that provides statistical guarantees for scientific reasoning validity through progressive absolute-coherent-factuality validation and decomposes scientific reasoning into atomic absolute-coherent-factuality units.

Dependency-Guided Code Generation: Structured Matrix Decomposition and Consistency-Guided Refinement

This work proposes a dependency-aware code generation framework that explicitly models interactions among code entities through a graph-based representation, and introduces a sparse triplet representation for strong dependencies, significantly improving storage efficiency and computational scalability.

PathSymphony: Harmonizing symbolic planning and Large Language Models for curriculum-guided mathematical reasoning