16 citations · 23 across the 7 of their papers we have counts for
8 papers
TAPS: Tool-Augmented Personalisation via Structured Tagging
Ekaterina Taktasheva, Jeff Dalton
Recent advancements in tool-augmented large language models have enabled them to interact with external tools, enhancing their ability to perform complex user tasks. However, exist…
RuBLiMP: Russian Benchmark of Linguistic Minimal Pairs
Ekaterina Taktasheva, Maxim Bazhukov, Kirill Koncha +3
Minimal pairs are a well-established approach to evaluating the grammatical knowledge of language models. However, existing resources for minimal pairs address a limited number of…
LUNA: A Framework for Language Understanding and Naturalness Assessment
Marat Saidov, Aleksandra Bakalova, Ekaterina Taktasheva +2
The evaluation of Natural Language Generation (NLG) models has gained increased attention, urging the development of metrics that evaluate various aspects of generated text. LUNA a…
A Family of Pretrained Transformer Language Models for Russian
Dmitry Zmitrovich, Alexander Abramov, Andrey Kalmykov +10
Transformer language models (LMs) are fundamental to NLP research methodologies and applications in various languages. However, developing such models specifically for the Russian…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
TAPE: Assessing Few-shot Russian Language Understanding
Ekaterina Taktasheva, Tatiana Shavrina, Alena Fenogenova +11
Recent advances in zero-shot and few-shot learning have shown promise for a scope of research and practical purposes. However, this fast-growing area lacks standardized evaluation…