Paper Group NANR 25
How Many Languages Can a Language Model Model?. Model Combination for Correcting Preposition Selection Errors. Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016). Fast Gated Neural Domain Adaptation: Language Model as a Case Study. Capturing Discriminative Attributes in a Distributional S …
How Many Languages Can a Language Model Model?
| Title | How Many Languages Can a Language Model Model? |
| Authors | Robert {"O}stling |
| Abstract | One of the purposes of the VarDial workshop series is to encourage research into NLP methods that treat human languages as a continuum, by designing models that exploit the similarities between languages and variants. In my work, I am using a continuous vector representation of languages that allows modeling and exploring the language continuum in a very direct way. The basic tool for this is a character-based recurrent neural network language model conditioned on language vectors whose values are learned during training. By feeding the model Bible translations in a thousand languages, not only does the learned vector space capture language similarity, but by interpolating between the learned vectors it is possible to generate text in unattested intermediate forms between the training languages. |
| Tasks | Language Modelling, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4808/ |
| https://www.aclweb.org/anthology/W16-4808 | |
| PWC | https://paperswithcode.com/paper/how-many-languages-can-a-language-model-model |
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Model Combination for Correcting Preposition Selection Errors
| Title | Model Combination for Correcting Preposition Selection Errors |
| Authors | Nitin Madnani, Michael Heilman, Aoife Cahill |
| Abstract | |
| Tasks | Grammatical Error Correction, Grammatical Error Detection, Language Modelling |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0515/ |
| https://www.aclweb.org/anthology/W16-0515 | |
| PWC | https://paperswithcode.com/paper/model-combination-for-correcting-preposition |
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Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016)
| Title | Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016) |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5100/ |
| https://www.aclweb.org/anthology/W16-5100 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-fifth-workshop-on-building |
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Fast Gated Neural Domain Adaptation: Language Model as a Case Study
| Title | Fast Gated Neural Domain Adaptation: Language Model as a Case Study |
| Authors | Jian Zhang, Xiaofeng Wu, Andy Way, Qun Liu |
| Abstract | Neural network training has been shown to be advantageous in many natural language processing applications, such as language modelling or machine translation. In this paper, we describe in detail a novel domain adaptation mechanism in neural network training. Instead of learning and adapting the neural network on millions of training sentences {–} which can be very time-consuming or even infeasible in some cases {–} we design a domain adaptation gating mechanism which can be used in recurrent neural networks and quickly learn the out-of-domain knowledge directly from the word vector representations with little speed overhead. In our experiments, we use the recurrent neural network language model (LM) as a case study. We show that the neural LM perplexity can be reduced by 7.395 and 12.011 using the proposed domain adaptation mechanism on the Penn Treebank and News data, respectively. Furthermore, we show that using the domain-adapted neural LM to re-rank the statistical machine translation n-best list on the French-to-English language pair can significantly improve translation quality. |
| Tasks | Domain Adaptation, Language Modelling, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1131/ |
| https://www.aclweb.org/anthology/C16-1131 | |
| PWC | https://paperswithcode.com/paper/fast-gated-neural-domain-adaptation-language |
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Capturing Discriminative Attributes in a Distributional Space: Task Proposal
| Title | Capturing Discriminative Attributes in a Distributional Space: Task Proposal |
| Authors | Alicia Krebs, Denis Paperno |
| Abstract | |
| Tasks | Semantic Textual Similarity |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2509/ |
| https://www.aclweb.org/anthology/W16-2509 | |
| PWC | https://paperswithcode.com/paper/capturing-discriminative-attributes-in-a |
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ECNU at SemEval-2016 Task 3: Exploring Traditional Method and Deep Learning Method for Question Retrieval and Answer Ranking in Community Question Answering
| Title | ECNU at SemEval-2016 Task 3: Exploring Traditional Method and Deep Learning Method for Question Retrieval and Answer Ranking in Community Question Answering |
| Authors | Guoshun Wu, Man Lan |
| Abstract | |
| Tasks | Community Question Answering, Question Answering, Question Similarity, Semantic Textual Similarity |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1135/ |
| https://www.aclweb.org/anthology/S16-1135 | |
| PWC | https://paperswithcode.com/paper/ecnu-at-semeval-2016-task-3-exploring |
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Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2016)
| Title | Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2016) |
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| Abstract | |
| Tasks | Coreference Resolution |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0700/ |
| https://www.aclweb.org/anthology/W16-0700 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-workshop-on-coreference |
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Unsupervised Text Recap Extraction for TV Series
| Title | Unsupervised Text Recap Extraction for TV Series |
| Authors | Hongliang Yu, Shikun Zhang, Louis-Philippe Morency |
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| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1185/ |
| https://www.aclweb.org/anthology/D16-1185 | |
| PWC | https://paperswithcode.com/paper/unsupervised-text-recap-extraction-for-tv |
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On- and Off-Topic Classification and Semantic Annotation of User-Generated Software Requirements
| Title | On- and Off-Topic Classification and Semantic Annotation of User-Generated Software Requirements |
| Authors | Markus Dollmann, Michaela Geierhos |
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| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1186/ |
| https://www.aclweb.org/anthology/D16-1186 | |
| PWC | https://paperswithcode.com/paper/on-and-off-topic-classification-and-semantic |
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The OnForumS corpus from the Shared Task on Online Forum Summarisation at MultiLing 2015
| Title | The OnForumS corpus from the Shared Task on Online Forum Summarisation at MultiLing 2015 |
| Authors | Mijail Kabadjov, Udo Kruschwitz, Massimo Poesio, Josef Steinberger, Jorge Valderrama, Hugo Zaragoza |
| Abstract | In this paper we present the OnForumS corpus developed for the shared task of the same name on Online Forum Summarisation (OnForumS at MultiLing{'}15). The corpus consists of a set of news articles with associated readers{'} comments from The Guardian (English) and La Repubblica (Italian). It comes with four levels of annotation: argument structure, comment-article linking, sentiment and coreference. The former three were produced through crowdsourcing, whereas the latter, by an experienced annotator using a mature annotation scheme. Given its annotation breadth, we believe the corpus will prove a useful resource in stimulating and furthering research in the areas of Argumentation Mining, Summarisation, Sentiment, Coreference and the interlinks therein. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1131/ |
| https://www.aclweb.org/anthology/L16-1131 | |
| PWC | https://paperswithcode.com/paper/the-onforums-corpus-from-the-shared-task-on |
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IITP English-Hindi Machine Translation System at WAT 2016
| Title | IITP English-Hindi Machine Translation System at WAT 2016 |
| Authors | Sukanta Sen, Debajyoty Banik, Asif Ekbal, Pushpak Bhattacharyya |
| Abstract | In this paper we describe the system that we develop as part of our participation in WAT 2016. We develop a system based on hierarchical phrase-based SMT for English to Hindi language pair. We perform re-ordering and augment bilingual dictionary to improve the performance. As a baseline we use a phrase-based SMT model. The MT models are fine-tuned on the development set, and the best configurations are used to report the evaluation on the test set. Experiments show the BLEU of 13.71 on the benchmark test data. This is better compared to the official baseline BLEU score of 10.79. |
| Tasks | Language Modelling, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4622/ |
| https://www.aclweb.org/anthology/W16-4622 | |
| PWC | https://paperswithcode.com/paper/iitp-english-hindi-machine-translation-system |
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A Hierarchical Neural Network for Information Extraction of Product Attribute and Condition Sentences
| Title | A Hierarchical Neural Network for Information Extraction of Product Attribute and Condition Sentences |
| Authors | Yukinori Homma, Kugatsu Sadamitsu, Kyosuke Nishida, Ryuichiro Higashinaka, Hisako Asano, Yoshihiro Matsuo |
| Abstract | This paper describes a hierarchical neural network we propose for sentence classification to extract product information from product documents. The network classifies each sentence in a document into attribute and condition classes on the basis of word sequences and sentence sequences in the document. Experimental results showed the method using the proposed network significantly outperformed baseline methods by taking semantic representation of word and sentence sequential data into account. We also evaluated the network with two different product domains (insurance and tourism domains) and found that it was effective for both the domains. |
| Tasks | Product Recommendation, Question Answering, Sentence Classification |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4403/ |
| https://www.aclweb.org/anthology/W16-4403 | |
| PWC | https://paperswithcode.com/paper/a-hierarchical-neural-network-for-information |
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Designing smoothing functions for improved worst-case competitive ratio in online optimization
| Title | Designing smoothing functions for improved worst-case competitive ratio in online optimization |
| Authors | Reza Eghbali, Maryam Fazel |
| Abstract | Online optimization covers problems such as online resource allocation, online bipartite matching, adwords (a central problem in e-commerce and advertising), and adwords with separable concave returns. We analyze the worst case competitive ratio of two primal-dual algorithms for a class of online convex (conic) optimization problems that contains the previous examples as special cases defined on the positive orthant. We derive a sufficient condition on the objective function that guarantees a constant worst case competitive ratio (greater than or equal to $\frac{1}{2}$) for monotone objective functions. We provide new examples of online problems on the positive orthant % and the positive semidefinite cone that satisfy the sufficient condition. We show how smoothing can improve the competitive ratio of these algorithms, and in particular for separable functions, we show that the optimal smoothing can be derived by solving a convex optimization problem. This result allows us to directly optimize the competitive ratio bound over a class of smoothing functions, and hence design effective smoothing customized for a given cost function. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6073-designing-smoothing-functions-for-improved-worst-case-competitive-ratio-in-online-optimization |
| http://papers.nips.cc/paper/6073-designing-smoothing-functions-for-improved-worst-case-competitive-ratio-in-online-optimization.pdf | |
| PWC | https://paperswithcode.com/paper/designing-smoothing-functions-for-improved |
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Multimodal Use of an Upper-Level Event Ontology
| Title | Multimodal Use of an Upper-Level Event Ontology |
| Authors | Claire Bonial, David Tahmoush, Susan Windisch Brown, Martha Palmer |
| Abstract | |
| Tasks | Question Answering, Semantic Role Labeling, Word Sense Disambiguation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-1003/ |
| https://www.aclweb.org/anthology/W16-1003 | |
| PWC | https://paperswithcode.com/paper/multimodal-use-of-an-upper-level-event |
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IHS-RD-Belarus at SemEval-2016 Task 9: Transition-based Chinese Semantic Dependency Parsing with Online Reordering and Bootstrapping.
| Title | IHS-RD-Belarus at SemEval-2016 Task 9: Transition-based Chinese Semantic Dependency Parsing with Online Reordering and Bootstrapping. |
| Authors | Artsiom Artsymenia, Palina Dounar, Maria Yermakovich |
| Abstract | |
| Tasks | Dependency Parsing, Semantic Dependency Parsing, Semantic Parsing |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1187/ |
| https://www.aclweb.org/anthology/S16-1187 | |
| PWC | https://paperswithcode.com/paper/ihs-rd-belarus-at-semeval-2016-task-9 |
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