| Using linguistic activity in social networks to predict and interpret dark psychological traits A Moskvichev, M Dubova, S Menshov, A Filchenkov Artificial Intelligence and Natural Language: 6th Conference, AINL 2017, St …, 2018 | 13 | 2018 |
| Against theory-motivated experimentation in science M Dubova, A Moskvichev, K Zollman MetaArXiv. June 24, 2022 | 5 | 2022 |
| Updater-extractor architecture for inductive world state representations A Moskvichev, JA Liu arXiv preprint arXiv:2104.05500, 2021 | 5 | 2021 |
| Reinforcement communication learning in different social network structures M Dubova, A Moskvichev, R Goldstone arXiv preprint arXiv:2007.09820, 2020 | 5 | 2020 |
| Effects of supervision, population size, and self-play on multi-agent reinforcement learning to communicate M Dubova, A Moskvichev Artificial Life Conference Proceedings 32, 678-686, 2020 | 5 | 2020 |
| The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain A Moskvichev, VV Odouard, M Mitchell arXiv preprint arXiv:2305.07141, 2023 | 4 | 2023 |
| A Picture is Worth 7.17 Words: Learning Categories from Examples and Definitions. A Moskvichev, R Tikhonov, M Steyvers CogSci, 2406-2412, 2019 | 3 | 2019 |
| Word Games as milestones for NLP research A Moskvichev, M Steyvers Proceedings of Workshop on Games and Natural Language Processing, 2019 | 2 | 2019 |
| Adaptation Aftereffects as a Result of Bayesian Categorization. M Dubova, A Moskvichev CogSci, 1669-1675, 2019 | 2 | 2019 |
| Data augmentation method for the image sentiment analysis A Rakovsky, A Moskvichev, A Filchenkov Proceeding of the AINL FRUCT 2016 Conference, Saint Petersburg, 106-109, 2016 | 2 | 2016 |
| Towards a Linguistic Model of Stress, Well. being and Dark Traits in Russian Facebook Texts P Panicheva, V Ivanov, A Moskvichev, O Bogolyubova, Y Ledovaya Proceeding of the AINL-ISMW FRUCT Conference 7, 2015 | 1 | 2015 |
| Teaching categories via examples and explanations A Moskivchev, R Tikhonov, M Steyvers Cognition 238, 105511, 2023 | | 2023 |
| Narrative XL: A Large-scale Dataset For Long-Term Memory Models A Moskvichev, KV Mai arXiv preprint arXiv:2305.13877, 2023 | | 2023 |
| Language-Based Learning: Cognitive and Computational Perspective A Moskvichev University of California, Irvine, 2022 | | 2022 |
| Category learning in preschool and primary school children: The use of rule-based and similarity-based strategies R Tikhonov, A Moskvichev, A Kotov Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | | 2021 |
| WHAT DO DARK PERSONALITIES WRITE ON FACEBOOK: AN INTERDISCIPLINARY STUDY OF SOCIAL NETWORK USERS BEHAVIOR Y Ledovaya, P Panicheva, R Tikhonov, O Bogolyubova, A Moskvichev XVI EUROPEAN CONGRESS OF PSYCHOLOGY, 1314-1314, 2019 | | 2019 |
| СРАВНЕНИЕ ОСОБЕННОСТЕЙ НАУЧЕНИЯ «ОТ ПРОСТОГО К СЛОЖНОМУ» И «ОТ СЛОЖНОГО К ПРОСТОМУ»(на примере задач перекодировки) АК МОСКВИЧЕВ, ИА ГОРБУНОВ Научные исследования выпускников факультета психологии СПбГУ 2, 195-201, 2014 | | 2014 |
| Enforcing Compositionality in Sentence Embedding Models A Moskvichev, M Steyvers | | |
