6 papers
SONAR-LLM: Autoregressive Transformer that Thinks in Sentence Embeddings and Speaks in Tokens
Nikita Dragunov, Temurbek Rahmatullaev, Elizaveta Goncharova +5
The recently proposed Large Concept Model (LCM) generates text by predicting a sequence of sentence-level embeddings and training with either mean-squared error or diffusion object…
NoReGeo: Non-Reasoning Geometry Benchmark
Irina Abdullaeva, Anton Vasiliuk, Elizaveta Goncharova +4
We present NoReGeo, a novel benchmark designed to evaluate the intrinsic geometric understanding of large language models (LLMs) without relying on reasoning or algebraic computati…
Universal Adversarial Attack on Aligned Multimodal LLMs
Temurbek Rahmatullaev, Polina Druzhinina, Nikita Kurdiukov +3
We propose a universal adversarial attack on multimodal Large Language Models (LLMs) that leverages a single optimized image to override alignment safeguards across diverse queries…
On consecutive factors of the lower central series of right-angled Coxeter groups
Yakov Veryovkin, Temur Rahmatullaev
We study the lower central series of the right-angled Coxeter group and the corresponding associated graded Lie algebra and describe the basis of…
LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers
Anton Razzhigaev, Matvey Mikhalchuk, Temurbek Rahmatullaev +4
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…
Polyhedral products, graph products and p-central series
Taras Panov, Temurbek Rahmatullaev
We relate polyhedral products of topological spaces to graph products of groups. The loop homology algebras of polyhedral products are identified with the universal enveloping alge…