3 papers
cs.CL2025
Enhancing Transformer-Based Rerankers with Synthetic Data and LLM-Based Supervision
Dimitar Peshevski, Kiril Blazhevski, Martin Popovski +1
Effective document reranking is essential for improving search relevance across diverse applications. While Large Language Models (LLMs) excel at reranking due to their deep semant…
cs.LG2022
Explainable Landscape Analysis in Automated Algorithm Performance Prediction
Risto Trajanov, Stefan Dimeski, Martin Popovski +2
Predicting the performance of an optimization algorithm on a new problem instance is crucial in order to select the most appropriate algorithm for solving that problem instance. Fo…
cs.NE2021
Explainable Landscape-Aware Optimization Performance Prediction
Risto Trajanov, Stefan Dimeski, Martin Popovski +2
Efficient solving of an unseen optimization problem is related to appropriate selection of an optimization algorithm and its hyper-parameters. For this purpose, automated algorithm…