Alexandre Klementiev


2019

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Inducing Document Structure for Aspect-based Summarization
Lea Frermann | Alexandre Klementiev
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Automatic summarization is typically treated as a 1-to-1 mapping from document to summary. Documents such as news articles, however, are structured and often cover multiple topics or aspects; and readers may be interested in only some of them. We tackle the task of aspect-based summarization, where, given a document and a target aspect, our models generate a summary centered around the aspect. We induce latent document structure jointly with an abstractive summarization objective, and train our models in a scalable synthetic setup. In addition to improvements in summarization over topic-agnostic baselines, we demonstrate the benefit of the learnt document structure: we show that our models (a) learn to accurately segment documents by aspect; (b) can leverage the structure to produce both abstractive and extractive aspect-based summaries; and (c) that structure is particularly advantageous for summarizing long documents. All results transfer from synthetic training documents to natural news articles from CNN/Daily Mail and RCV1.

2012

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Crosslingual Induction of Semantic Roles
Ivan Titov | Alexandre Klementiev
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Inducing Crosslingual Distributed Representations of Words
Alexandre Klementiev | Ivan Titov | Binod Bhattarai
Proceedings of COLING 2012

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Semi-Supervised Semantic Role Labeling: Approaching from an Unsupervised Perspective
Ivan Titov | Alexandre Klementiev
Proceedings of COLING 2012

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Unsupervised Induction of Frame-Semantic Representations
Ashutosh Modi | Ivan Titov | Alexandre Klementiev
Proceedings of the NAACL-HLT Workshop on the Induction of Linguistic Structure

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A Bayesian Approach to Unsupervised Semantic Role Induction
Ivan Titov | Alexandre Klementiev
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

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Toward Statistical Machine Translation without Parallel Corpora
Alexandre Klementiev | Ann Irvine | Chris Callison-Burch | David Yarowsky
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

2011

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A Bayesian Model for Unsupervised Semantic Parsing
Ivan Titov | Alexandre Klementiev
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2010

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Using Mechanical Turk to Annotate Lexicons for Less Commonly Used Languages
Ann Irvine | Alexandre Klementiev
Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk

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Transliterating From All Languages
Ann Irvine | Chris Callison-Burch | Alexandre Klementiev
Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers

Much of the previous work on transliteration has depended on resources and attributes specific to particular language pairs. In this work, rather than focus on a single language pair, we create robust models for transliterating from all languages in a large, diverse set to English. We create training data for 150 languages by mining name pairs from Wikipedia. We train 13 systems and analyze the effects of the amount of training data on transliteration performance. We also present an analysis of the types of errors that the systems make. Our analyses are particularly valuable for building machine translation systems for low resource languages, where creating and integrating a transliteration module for a language with few NLP resources may provide substantial gains in translation performance.

2008

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Using Contextual Speller Techniques and Language Modeling for ESL Error Correction
Michael Gamon | Jianfeng Gao | Chris Brockett | Alexandre Klementiev | William B. Dolan | Dmitriy Belenko | Lucy Vanderwende
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I

2006

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Weakly Supervised Named Entity Transliteration and Discovery from Multilingual Comparable Corpora
Alexandre Klementiev | Dan Roth
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

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Named Entity Transliteration and Discovery from Multilingual Comparable Corpora
Alexandre Klementiev | Dan Roth
Proceedings of the Human Language Technology Conference of the NAACL, Main Conference