32 citations · 168 across the 19 of their papers we have counts for
14 papers · 1 filter
Smotrom tvoja pa ander drogoj verden! Resurrecting Dead Pidgin with Generative Models: Russenorsk Case Study
Alexey Tikhonov, Sergei Shteiner, Anna Bykova +1
Russenorsk, a pidgin language historically used in trade interactions between Russian and Norwegian speakers, represents a unique linguistic phenomenon. In this paper, we attempt t…
Individuation in Neural Models with and without Visual Grounding
Alexey Tikhonov, Lisa Bylinina, Ivan P. Yamshchikov
We show differences between a language-and-vision model CLIP and two text-only models - FastText and SBERT - when it comes to the encoding of individuation information. We study la…
Knowledge Graph Representation for Political Information Sources
Tinatin Osmonova, Alexey Tikhonov, Ivan P. Yamshchikov
With the rise of computational social science, many scholars utilize data analysis and natural language processing tools to analyze social media, news articles, and other accessibl…
BERT in Plutarch's Shadows
Ivan P. Yamshchikov, Alexey Tikhonov, Yorgos Pantis +2
The extensive surviving corpus of the ancient scholar Plutarch of Chaeronea (ca. 45-120 CE) also contains several texts which, according to current scholarly opinion, did not origi…
Rethinking Crowd Sourcing for Semantic Similarity
Shaul Solomon, Adam Cohn, Hernan Rosenblum +2
Estimation of semantic similarity is crucial for a variety of natural language processing (NLP) tasks. In the absence of a general theory of semantic information, many papers rely…
DYPLODOC: Dynamic Plots for Document Classification
Anastasia Malysheva, Alexey Tikhonov, Ivan P. Yamshchikov
Narrative generation and analysis are still on the fringe of modern natural language processing yet are crucial in a variety of applications. This paper proposes a feature extracti…
Paranoid Transformer: Reading Narrative of Madness as Computational Approach to Creativity
Yana Agafonova, Alexey Tikhonov, Ivan P. Yamshchikov
This papers revisits the receptive theory in context of computational creativity. It presents a case study of a Paranoid Transformer - a fully autonomous text generation engine wit…
Intuitive Contrasting Map for Antonym Embeddings
Igor Samenko, Alexey Tikhonov, Ivan P. Yamshchikov
This paper shows that, modern word embeddings contain information that distinguishes synonyms and antonyms despite small cosine similarities between corresponding vectors. This inf…
Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric
Ivan P. Yamshchikov, Viacheslav Shibaev, Nikolay Khlebnikov +1
The rapid development of such natural language processing tasks as style transfer, paraphrase, and machine translation often calls for the use of semantic similarity metrics. In re…
It Means More if It Sounds Good: Yet Another Hypothesis Concerning the Evolution of Polysemous Words
Ivan P. Yamshchikov, Cyrille Merleau Nono Saha, Igor Samenko +1
This position paper looks into the formation of language and shows ties between structural properties of the words in the English language and their polysemy. Using Ollivier-Ricci…
Decomposing Textual Information For Style Transfer
Ivan P. Yamshchikov, Viacheslav Shibaev, Aleksander Nagaev +2
This paper focuses on latent representations that could effectively decompose different aspects of textual information. Using a framework of style transfer for texts, we propose se…
Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites
Alexey Tikhonov, Viacheslav Shibaev, Aleksander Nagaev +2
This paper shows that standard assessment methodology for style transfer has several significant problems. First, the standard metrics for style accuracy and semantics preservation…
What is wrong with style transfer for texts?
Alexey Tikhonov, Ivan P. Yamshchikov
A number of recent machine learning papers work with an automated style transfer for texts and, counter to intuition, demonstrate that there is no consensus formulation of this NLP…
Guess who? Multilingual approach for the automated generation of author-stylized poetry
Alexey Tikhonov, Ivan P. Yamshchikov
This paper addresses the problem of stylized text generation in a multilingual setup. A version of a language model based on a long short-term memory (LSTM) artificial neural netwo…