Author

Eduard Tulchinskii

2 papers indexed here

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#artificial intelligence Conference Feb 2025

Quantifying Logical Consistency in Transformers via Query-Key Alignment

This paper proposes a novel, lightweight evaluation strategy for logical reasoning that uses query-key alignments inside transformer attention heads that reveals latent representations that reliably separate valid from invalid inferences, offering a scalable alternative to traditional ablation-based techniques.

Eduard Tulchinskii, Anastasia Voznyuk, Laida Kushnareva et al. · Conference on Empirical Meth... · 0 citations

#artificial intelligence Preprint Sep 2026

CodeTD: Topology of Attention Detects Hallucinations in Code LLMs

This paper introduces CodeTD -- the first approach to pre-execution assessment of code correctness based on topological data analysis (TDA) of Code LLMs' attention maps, which quantifies prompt-generation mismatch using topological patterns of attention maps.

D. Voronkova, I. Trofimov, Anton Dmitriev et al. · 0 citations