1 citations · 1 across the 9 of their papers we have counts for
4 papers · 2 filters
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…
Improving Constraint Models with LLM Agents
Florentina Voboril, Stefan Szeider
The runtime of Constraint Programming (CP) solvers is highly sensitive to modeling choices, such as symmetry breaking, implied constraints, global constraints, constraint reformula…
ASP-Bench: From Natural Language to Logic Programs
Stefan Szeider
Automating the translation of natural-language specifications into logic programs is a challenging task that affects neurosymbolic engineering. We present ASP-Bench, a benchmark co…