works on

From the 1 of 13 linked papers with an AI index.

collaborators

13 papers

cs.AI2026

Neurosymbolic Discovery of Algebraic Graph Constructions

David Seka, Stefan Szeider

There are several methods for searching for graphs with prescribed properties, such as SAT solvers and specialized generators. These methods return the result as raw data: an adjac…

cs.AI2026

LeanCSP: A Framework for Certifying Constraint Reformulation and Solving in Lean

Pablo Manrique, Stefan Szeider

The paper presents LeanCSP, a framework built in the Lean theorem prover that can formally verify constraint reformulations and certify solver results for constraint problems, prov…

cs.AI2026

Algorithm Selection with Zero Domain Knowledge via Text Embeddings

Stefan Szeider

We propose a feature-free approach to algorithm selection: instead of hand-crafted instance features, we use pretrained text embeddings. Our method, ZeroFolio, proceeds in three st…

cs.LO2026

LRAT-Catcher: Importing SAT Solver Certificates into Lean4 by Reflection

Stefan Szeider

SAT solvers settle combinatorial problems beyond the reach of interactive theorem provers and produce LRAT certificates for independent verification. We present LRAT-Catcher, a sta…

cs.LO2026

Streamliners for Answer Set Programming

Florentina Voboril, Martin Gebser, Stefan Szeider +1

Streamliner constraints reduce the search space of combinatorial problems by ruling out portions of the solution space. We adapt the StreamLLM approach, which uses Large Language M…

cs.AI2026

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…