Zangir Iklassov

According to our database, Zangir Iklassov authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Measuring AI Reasoning: A Guide for Researchers.

Munachiso Nwadike, Zangir Iklassov, Kareem Ali, Rifo Genadi, Kentaro Inui

CoRR, May, 2026

2025

The AI Data Scientist.

Farkhad Akimov, Munachiso Nwadike, Zangir Iklassov, Martin Takác

CoRR, August, 2025

LLM-BABYBENCH: Understanding and Evaluating Grounded Planning and Reasoning in LLMs.

Omar Choukrani, Idriss Malek, Daniil Orel, Zhuohan Xie, Zangir Iklassov, Martin Takác, Salem Lahlou

CoRR, May, 2025

RECALL: Library-Like Behavior In Language Models is Enhanced by Self-Referencing Causal Cycles.

Munachiso Nwadike, Zangir Iklassov, Toluwani Aremu, Tatsuya Hiraoka, Velibor Bojkovic, Benjamin Heinzerling, Hilal Alqaubeh, Martin Takác, Kentaro Inui

CoRR, January, 2025

SVRPBench: A Realistic Benchmark for Stochastic Vehicle Routing Problem.

Ahmed Heakl, Yahia Salaheldin Shaaban, Salem Lahlou, Martin Takác, Zangir Iklassov

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Library-Like Behavior In Language Models is Enhanced by Self-Referencing Causal Cycles.

Munachiso Nwadike, Zangir Iklassov, Toluwani Aremu, Tatsuya Hiraoka, Benjamin Heinzerling, Velibor Bojkovic, Hilal AlQuabeh, Martin Takác, Kentaro Inui

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

A Decade of Deep Learning: A Survey on The Magnificent Seven.

Dilshod Azizov, Muhammad Arslan Manzoor, Velibor Bojkovic, Yingxu Wang, Zixiao Wang, Zangir Iklassov, Kailong Zhao, Liang Li, Siwei Liu, Yu Zhong, Wei Liu, Shangsong Liang

CoRR, 2024

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows.

Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takác

CoRR, 2024

Self-Guiding Exploration for Combinatorial Problems.

Zangir Iklassov, Yali Du, Farkhad Akimov, Martin Takác

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands.

Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takác

IEEE Access, 2023

On the Study of Curriculum Learning for Inferring Dispatching Policies on the Job Shop Scheduling.

Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal Ochoa de Retana, Martin Takác

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem.

Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takác

Proceedings of the Asian Conference on Machine Learning, 2023

2022

Learning to generalize Dispatching rules on the Job Shop Scheduling.

Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal, Martin Takác

CoRR, 2022

AI for Porosity and Permeability Prediction from Geologic Core X-Ray Micro-Tomography.

Zangir Iklassov, Dmitrii Medvedev, Otabek Nazarov

CoRR, 2022

Robust Reinforcement Learning on Graphs for Logistics optimization.

Zangir Iklassov, Dmitrii Medvedev

CoRR, 2022

2019

Analytics of Heterogeneous Breast Cancer Data Using Neuroevolution.

Beibit Abdikenov, Zangir Iklassov, Askhat Sharipov, Shahid Hussain, Prashant Kumar Jamwal

IEEE Access, 2019