collaborators

5 papers

cs.AI2026

Neuro-Evolved Heuristics for Variable Gapped Common Subsequence Identification

Marko Djukanović, Christian Blum, Aleksandar Kartelj +2

This study addresses the Variable Gapped Longest Common Subsequence Problem (VGLCSP), a variant of the classical longest common subsequence problem with additional gap constraints…

cs.SI2026

Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performance

Maryam Gholami Shiri, Ivana Krminac, Marko Djukanović +3

Benchmarking shortest-path algorithms is commonly based on aggregate performance over heterogeneous graph sets, which limits insight into how different search paradigms react to in…

cs.CL2026

Consistent and Distinctive: LLM Benchmark Efficiency via Maximum Independent Set Prompt Selection on Similarity Graphs

Denica Kjorvezir, Marko Djukanović, Ana Gjorgjevikj +2

Evaluating large language models (LLMs) across comprehensive benchmarks is expensive and time-consuming. We propose a graph-based prompt selection framework that models each benchm…

cs.AI2026

On Solving the Multiple Variable Gapped Longest Common Subsequence Problem

Marko Djukanović, Nikola Balaban, Christian Blum +3

This paper addresses the Variable Gapped Longest Common Subsequence (VGLCS) problem, a generalization of the classical LCS problem involving flexible gap constraints between consec…

cs.AI2024

A Learning Search Algorithm for the Restricted Longest Common Subsequence Problem

Marko Djukanović, Jaume Reixach, Ana Nikolikj +3

This paper addresses the Restricted Longest Common Subsequence (RLCS) problem, an extension of the well-known Longest Common Subsequence (LCS) problem. This problem has significant…