no code implementations • RANLP 2021 • Boris Galitsky, Dmitry Ilvovsky, Elizaveta Goncharova
Machine reading comprehension (MRC) is one of the most challenging tasks in natural language processing domain.
no code implementations • EcomNLP (COLING) 2020 • Boris Galitsky, Dmitry Ilvovsky, Elizaveta Goncharova
Information retrieval chatbots are widely used as assistants, to help users formulate their requirements about the products they want to purchase, and navigate to the set of items that satisfies their requirements in the best way.
1 code implementation • 19 May 2024 • Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova, Nikolai Gerasimenko, Ivan Oseledets, Denis Dimitrov, Andrey Kuznetsov
This regularization improves performance metrics on benchmarks like Tiny Stories and SuperGLUE and as well successfully decreases the linearity of the models.
2 code implementations • 9 Apr 2024 • Elizaveta Goncharova, Anton Razzhigaev, Matvey Mikhalchuk, Maxim Kurkin, Irina Abdullaeva, Matvey Skripkin, Ivan Oseledets, Denis Dimitrov, Andrey Kuznetsov
We propose an \textit{OmniFusion} model based on a pretrained LLM and adapters for visual modality.
Ranked #40 on Visual Question Answering on MM-Vet
1 code implementation • 9 Jan 2024 • Alena Fenogenova, Artem Chervyakov, Nikita Martynov, Anastasia Kozlova, Maria Tikhonova, Albina Akhmetgareeva, Anton Emelyanov, Denis Shevelev, Pavel Lebedev, Leonid Sinev, Ulyana Isaeva, Katerina Kolomeytseva, Daniil Moskovskiy, Elizaveta Goncharova, Nikita Savushkin, Polina Mikhailova, Denis Dimitrov, Alexander Panchenko, Sergei Markov
To address these issues, we introduce an open Multimodal Evaluation of Russian-language Architectures (MERA), a new instruction benchmark for evaluating foundation models oriented towards the Russian language.
no code implementations • 13 Nov 2023 • Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
Recent advancements in the capabilities of large language models (LLMs) have paved the way for a myriad of groundbreaking applications in various fields.
no code implementations • 10 Nov 2023 • Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova, Ivan Oseledets, Denis Dimitrov, Andrey Kuznetsov
In this study, we present an investigation into the anisotropy dynamics and intrinsic dimension of embeddings in transformer architectures, focusing on the dichotomy between encoders and decoders.
no code implementations • WS 2019 • Boris Galitsky, Dmitry Ilvovsky, Elizaveta Goncharova
We demo a chatbot that delivers content in the form of virtual dialogues automatically produced from plain texts extracted and selected from documents.
no code implementations • RANLP 2019 • Boris Galitsky, Dmitry Ilvovsky, Elizaveta Goncharova
We present a chatbot that delivers content in the form of virtual dialogues automatically produced from the plain texts that are extracted and selected from the documents.