2 citations · 5 across the 15 of their papers we have counts for
4 papers · 1 filter
Addressing Hallucinations in Language Models with Knowledge Graph Embeddings as an Additional Modality
Viktoriia Chekalina, Anton Razzhigaev, Elizaveta Goncharova +1
In this paper we present an approach to reduce hallucinations in Large Language Models (LLMs) by incorporating Knowledge Graphs (KGs) as an additional modality. Our method involves…
Your Transformer is Secretly Linear
Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova +4
This paper reveals a novel linear characteristic exclusive to transformer decoders, including models such as GPT, LLaMA, OPT, BLOOM and others. We analyze embedding transformations…
OmniFusion Technical Report
Elizaveta Goncharova, Anton Razzhigaev, Matvey Mikhalchuk +6
Last year, multimodal architectures served up a revolution in AI-based approaches and solutions, extending the capabilities of large language models (LLM). We propose an \textit{Om…
MERA: A Comprehensive LLM Evaluation in Russian
Alena Fenogenova, Artem Chervyakov, Nikita Martynov +16
Over the past few years, one of the most notable advancements in AI research has been in foundation models (FMs), headlined by the rise of language models (LMs). As the models' siz…