7 papers
Post-Pruning vs. Early Stopping: Which Works Better for Link Prediction with AnyBurl?
Thomas Eiter, Davide Soldà, Hai Xia
Rule-based link prediction combines symbolic and statistical artificial intelligence methods by inductively learning a set of rules from a knowledge graph (KG), with the aim of com…
Erdős-Gyárfás Balanced Five-Colorings
Hai Xia, Stefan Szeider
A coloring of the edges of a complete graph with colors is balanced if the edges among any vertices use all colors. Erdős and Gyárfás (1999) conjectured that for all…
Synthesizing Feature Extractors: An Agentic Approach for Algorithm Selection
Hai Xia, Carlos Ansótegui, Stefan Szeider
Algorithm selection for constraint satisfaction problems requires extracting features that capture problem structure. Manually designing feature extractors demands deep domain expe…
LLM-Guided Graph Generation for Structure-Based Local Improvement Methods
Hai Xia, Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider
Large neighborhood search normally selects a random subset of decision variables for iterative optimization. To efficiently solve various problems, researchers tend to design varia…
Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning
Haizhou Xia
Post-hoc repair of LLM mathematical reasoning introduces an asymmetric risk: fixing an incorrect reasoning trace is useful, but replacing a trace that was already correct can be ha…
Agentic Neurosymbolic Collaboration for Mathematical Discovery: A Case Study in Combinatorial Design
Hai Xia, Carla P. Gomes, Bart Selman +1
We study mathematical discovery through the lens of neurosymbolic reasoning, where an AI agent powered by a large language model (LLM), coupled with symbolic computation tools, and…
Smart Cubing for Graph Search: A Comparative Study
Markus Kirchweger, Hai Xia, Tomáš Peitl +1
Parallel solving via cube-and-conquer is a key method for scaling SAT solvers to hard instances. While cube-and-conquer has proven successful for pure SAT problems, notably the Pyt…