Mikhail Kozhevnikov


Automatic Prediction of Discourse Connectives
Eric Malmi | Daniele Pighin | Sebastian Krause | Mikhail Kozhevnikov
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


Redundancy Localization for the Conversationalization of Unstructured Responses
Sebastian Krause | Mikhail Kozhevnikov | Eric Malmi | Daniele Pighin
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

Conversational agents offer users a natural-language interface to accomplish tasks, entertain themselves, or access information. Informational dialogue is particularly challenging in that the agent has to hold a conversation on an open topic, and to achieve a reasonable coverage it generally needs to digest and present unstructured information from textual sources. Making responses based on such sources sound natural and fit appropriately into the conversation context is a topic of ongoing research, one of the key issues of which is preventing the agent’s responses from sounding repetitive. Targeting this issue, we propose a new task, known as redundancy localization, which aims to pinpoint semantic overlap between text passages. To help address it systematically, we formalize the task, prepare a public dataset with fine-grained redundancy labels, and propose a model utilizing a weak training signal defined over the results of a passage-retrieval system on web texts. The proposed model demonstrates superior performance compared to a state-of-the-art entailment model and yields encouraging results when applied to a real-world dialogue.


Revisiting Taxonomy Induction over Wikipedia
Amit Gupta | Francesco Piccinno | Mikhail Kozhevnikov | Marius Paşca | Daniele Pighin
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

Guided by multiple heuristics, a unified taxonomy of entities and categories is distilled from the Wikipedia category network. A comprehensive evaluation, based on the analysis of upward generalization paths, demonstrates that the taxonomy supports generalizations which are more than twice as accurate as the state of the art. The taxonomy is available at http://headstaxonomy.com.


Cross-lingual Model Transfer Using Feature Representation Projection
Mikhail Kozhevnikov | Ivan Titov
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)


Bootstrapping Semantic Role Labelers from Parallel Data
Mikhail Kozhevnikov | Ivan Titov
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity

Cross-lingual Transfer of Semantic Role Labeling Models
Mikhail Kozhevnikov | Ivan Titov
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)


Bootstrapping Semantic Analyzers from Non-Contradictory Texts
Ivan Titov | Mikhail Kozhevnikov
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics