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Zangir Iklassov

4 accepted papers

2025

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

ACL 2025long

We introduce the concept of the self-referencing causal cycle (abbreviated ReCall )—a mechanism that enables large language models (LLMs) to bypass the limitations of unidirectional causality, which underlies a phenomenon known as the reversal curse. When an LLM is prompted with sequential data, it…

2025

SVRPBench: A Realistic Benchmark for Stochastic Vehicle Routing Problem

NeurIPS 2025poster

Robust routing under uncertainty is central to real-world logistics, yet most benchmarks assume static, idealized settings. We present \texttt{SVRPBench}, the first open benchmark to capture high-fidelity stochastic dynamics in vehicle routing at urban scale. Spanning more than 500 instances with up…

Cited by 0SourcecodeScholar
2024

Self-Guiding Exploration for Combinatorial Problems

NeurIPS 2024poster

Large Language Models (LLMs) have become pivotal in addressing reasoning tasks across diverse domains, including arithmetic, commonsense, and symbolic reasoning. They utilize prompting techniques such as Exploration-of-Thought, Decomposition, and Refinement to effectively navigate and solve intricat…

2023

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

IJCAI 2023poster

This paper studies the use of Curriculum Learning on Reinforcement Learning (RL) to improve the performance of the dispatching policies learned on the Job-shop Scheduling Problem (JSP). Current works in the literature present a large optimality gap when learning end-to-end solutions on this problem.…

Cited by 10SourcePDFScholar