Temurbek Rahmatullaev — accepted AI-conference papers

2026

NoReGeo: Non-Reasoning Geometry Benchmark

Irina Abdullaeva, Anton Vasiliuk, Elizaveta Goncharova, Temurbek Rahmatullaev, Zagorulko Ivan, Maxim Kurkin +1

AAAI 2026technical

We present NoReGeo, a novel benchmark designed to evaluate the intrinsic geometric understanding of large language models (LLMs) without relying on reasoning or algebraic computation. Unlike existing benchmarks that primarily assess models

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2025

LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers

Anton Razzhigaev, Matvey Mikhalchuk, Temurbek Rahmatullaev, Elizaveta Goncharova, Polina Druzhinina, Ivan Oseledets +1

NAACL 2025findings

We introduce methods to quantify how Large Language Models (LLMs) encode and store contextual information, revealing that tokens often seen as minor (e.g., determiners, punctuation) carry surprisingly high context. Notably, removing these tokens — especially stopwords, articles, and commas — consist…

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