Paper Group NANR 41
TCL - a Lexicon of Turkish Discourse Connectives. Universal Domain Adaptation. Boosting Local Shape Matching for Dense 3D Face Correspondence. VerbNet Representations: Subevent Semantics for Transfer Verbs. A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information. A Blissymbolics Translation Sy …
TCL - a Lexicon of Turkish Discourse Connectives
| Title | TCL - a Lexicon of Turkish Discourse Connectives |
| Authors | Deniz Zeyrek, Kezban Ba{\c{s}}{\i}b{"u}y{"u}k |
| Abstract | It is known that discourse connectives are the most salient indicators of discourse relations. State-of-the-art parsers being developed to predict explicit discourse connectives exploit annotated discourse corpora but a lexicon of discourse connectives is also needed to enable further research in discourse structure and support the development of language technologies that use these structures for text understanding. This paper presents a lexicon of Turkish discourse connectives built by automatic means. The lexicon has the format of the German connective lexicon, DiMLex, where for each discourse connective, information about the connective{`}s orthographic variants, syntactic category and senses are provided along with sample relations. In this paper, we describe the data sources we used and the development steps of the lexicon. | |
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| Published | 2019-08-01 |
| URL | https://www.aclweb.org/anthology/W19-3308/ |
| https://www.aclweb.org/anthology/W19-3308 | |
| PWC | https://paperswithcode.com/paper/tcl-a-lexicon-of-turkish-discourse |
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Universal Domain Adaptation
| Title | Universal Domain Adaptation |
| Authors | Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan |
| Abstract | Domain adaptation aims to transfer knowledge in the presence of the domain gap. Existing domain adaptation methods rely on rich prior knowledge about the relationship between the label sets of source and target domains, which greatly limits their application in the wild. This paper introduces Universal Domain Adaptation (UDA) that requires no prior knowledge on the label sets. For a given source label set and a target label set, they may contain a common label set and hold a private label set respectively, bringing up an additional category gap. UDA requires a model to either (1) classify the target sample correctly if it is associated with a label in the common label set, or (2) mark it as “unknown” otherwise. More importantly, a UDA model should work stably against a wide spectrum of commonness (the proportion of the common label set over the complete label set) so that it can handle real-world problems with unknown target label sets. To solve the universal domain adaptation problem, we propose Universal Adaptation Network (UAN). It quantifies sample-level transferability to discover the common label set and the label sets private to each domain, thereby promoting the adaptation in the automatically discovered common label set and recognizing the “unknown” samples successfully. A thorough evaluation shows that UAN outperforms the state of the art closed set, partial and open set domain adaptation methods in the novel UDA setting. |
| Tasks | Domain Adaptation |
| Published | 2019-06-01 |
| URL | http://openaccess.thecvf.com/content_CVPR_2019/html/You_Universal_Domain_Adaptation_CVPR_2019_paper.html |
| http://openaccess.thecvf.com/content_CVPR_2019/papers/You_Universal_Domain_Adaptation_CVPR_2019_paper.pdf | |
| PWC | https://paperswithcode.com/paper/universal-domain-adaptation |
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Boosting Local Shape Matching for Dense 3D Face Correspondence
| Title | Boosting Local Shape Matching for Dense 3D Face Correspondence |
| Authors | Zhenfeng Fan, Xiyuan Hu, Chen Chen, Silong Peng |
| Abstract | Dense 3D face correspondence is a fundamental and challenging issue in the literature of 3D face analysis. Correspondence between two 3D faces can be viewed as a non-rigid registration problem that one deforms into the other, which is commonly guided by a few facial landmarks in many existing works. However, the current works seldom consider the problem of incoherent deformation caused by landmarks. In this paper, we explicitly formulate the deformation as locally rigid motions guided by some seed points, and the formulated deformation satisfies coherent local motions everywhere on a face. The seed points are initialized by a few landmarks, and are then augmented to boost shape matching between the template and the target face step by step, to finally achieve dense correspondence. In each step, we employ a hierarchical scheme for local shape registration, together with a Gaussian reweighting strategy for accurate matching of local features around the seed points. In our experiments, we evaluate the proposed method extensively on several datasets, including two publicly available ones: FRGC v2.0 and BU-3DFE. The experimental results demonstrate that our method can achieve accurate feature correspondence, coherent local shape motion, and compact data representation. These merits actually settle some important issues for practical applications, such as expressions, noise, and partial data. |
| Tasks | |
| Published | 2019-06-01 |
| URL | http://openaccess.thecvf.com/content_CVPR_2019/html/Fan_Boosting_Local_Shape_Matching_for_Dense_3D_Face_Correspondence_CVPR_2019_paper.html |
| http://openaccess.thecvf.com/content_CVPR_2019/papers/Fan_Boosting_Local_Shape_Matching_for_Dense_3D_Face_Correspondence_CVPR_2019_paper.pdf | |
| PWC | https://paperswithcode.com/paper/boosting-local-shape-matching-for-dense-3d |
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VerbNet Representations: Subevent Semantics for Transfer Verbs
| Title | VerbNet Representations: Subevent Semantics for Transfer Verbs |
| Authors | Susan Windisch Brown, Julia Bonn, James Gung, Annie Zaenen, James Pustejovsky, Martha Palmer |
| Abstract | This paper announces the release of a new version of the English lexical resource VerbNet with substantially revised semantic representations designed to facilitate computer planning and reasoning based on human language. We use the transfer of possession and transfer of information event representations to illustrate both the general framework of the representations and the types of nuances the new representations can capture. These representations use a Generative Lexicon-inspired subevent structure to track attributes of event participants across time, highlighting oppositions and temporal and causal relations among the subevents. |
| Tasks | |
| Published | 2019-08-01 |
| URL | https://www.aclweb.org/anthology/W19-3318/ |
| https://www.aclweb.org/anthology/W19-3318 | |
| PWC | https://paperswithcode.com/paper/verbnet-representations-subevent-semantics |
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A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information
| Title | A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information |
| Authors | Sofie Labat, Els Lefever |
| Abstract | This paper presents proof-of-concept experiments for combining orthographic and semantic information to distinguish cognates from non-cognates. To this end, a context-independent gold standard is developed by manually labelling English-Dutch pairs of cognates and false friends in bilingual term lists. These annotated cognate pairs are then used to train and evaluate a supervised binary classification system for the automatic detection of cognates. Two types of information sources are incorporated in the classifier: fifteen string similarity metrics capture form similarity between source and target words, while word embeddings model semantic similarity between the words. The experimental results show that even though the system already achieves good results by only incorporating orthographic information, the performance further improves by including semantic information in the form of embeddings. |
| Tasks | Semantic Similarity, Semantic Textual Similarity, Word Embeddings |
| Published | 2019-09-01 |
| URL | https://www.aclweb.org/anthology/R19-1071/ |
| https://www.aclweb.org/anthology/R19-1071 | |
| PWC | https://paperswithcode.com/paper/a-classification-based-approach-to-cognate |
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A Blissymbolics Translation System
| Title | A Blissymbolics Translation System |
| Authors | Usman Sohail, David Traum |
| Abstract | Blissymbolics (Bliss) is a pictographic writing system that is used by people with communication disorders. Bliss attempts to create a writing system that makes words easier to distinguish by using pictographic symbols that encapsulate meaning rather than sound, as the English alphabet does for example. Users of Bliss rely on human interpreters to use Bliss. We created a translation system from Bliss to natural English with the hopes of decreasing the reliance on human interpreters by the Bliss community. We first discuss the basic rules of Blissymbolics. Then we point out some of the challenges associated with developing computer assisted tools for Blissymbolics. Next we talk about our ongoing work in developing a translation system, including current limitations, and future work. We conclude with a set of examples showing the current capabilities of our translation system. |
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| Published | 2019-06-01 |
| URL | https://www.aclweb.org/anthology/W19-1705/ |
| https://www.aclweb.org/anthology/W19-1705 | |
| PWC | https://paperswithcode.com/paper/a-blissymbolics-translation-system |
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SUM-QE: a BERT-based Summary Quality Estimation Model
| Title | SUM-QE: a BERT-based Summary Quality Estimation Model |
| Authors | Stratos Xenouleas, Prodromos Malakasiotis, Marianna Apidianaki, Ion Androutsopoulos |
| Abstract | We propose SUM-QE, a novel Quality Estimation model for summarization based on BERT. The model addresses linguistic quality aspects that are only indirectly captured by content-based approaches to summary evaluation, without involving comparison with human references. SUM-QE achieves very high correlations with human ratings, outperforming simpler models addressing these linguistic aspects. Predictions of the SUM-QE model can be used for system development, and to inform users of the quality of automatically produced summaries and other types of generated text. |
| Tasks | |
| Published | 2019-11-01 |
| URL | https://www.aclweb.org/anthology/D19-1618/ |
| https://www.aclweb.org/anthology/D19-1618 | |
| PWC | https://paperswithcode.com/paper/sum-qe-a-bert-based-summary-quality |
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What is the impact of raw MT on Japanese users of Word: preliminary results of a usability study using eye-tracking
| Title | What is the impact of raw MT on Japanese users of Word: preliminary results of a usability study using eye-tracking |
| Authors | Ana Guerberof Arenas, Joss Moorkens, Sharon O{'}Brien |
| Abstract | |
| Tasks | Eye Tracking |
| Published | 2019-08-01 |
| URL | https://www.aclweb.org/anthology/W19-6607/ |
| https://www.aclweb.org/anthology/W19-6607 | |
| PWC | https://paperswithcode.com/paper/what-is-the-impact-of-raw-mt-on-japanese |
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Exploring Cognitive Effort in Written Translation of Chinese Neologisms: An Eye-tracking and Keylogging Study
| Title | Exploring Cognitive Effort in Written Translation of Chinese Neologisms: An Eye-tracking and Keylogging Study |
| Authors | Jinjin Chen, Defeng Li, Victoria Lei |
| Abstract | |
| Tasks | Eye Tracking |
| Published | 2019-08-01 |
| URL | https://www.aclweb.org/anthology/W19-7012/ |
| https://www.aclweb.org/anthology/W19-7012 | |
| PWC | https://paperswithcode.com/paper/exploring-cognitive-effort-in-written |
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Proceedings of the First Workshop on Narrative Understanding
| Title | Proceedings of the First Workshop on Narrative Understanding |
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| Abstract | |
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| Published | 2019-06-01 |
| URL | https://www.aclweb.org/anthology/W19-2400/ |
| https://www.aclweb.org/anthology/W19-2400 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-first-workshop-on-11 |
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Perceiving the arrow of time in autoregressive motion
| Title | Perceiving the arrow of time in autoregressive motion |
| Authors | Kristof Meding, Dominik Janzing, Bernhard Schölkopf, Felix A. Wichmann |
| Abstract | Understanding the principles of causal inference in the visual system has a long history at least since the seminal studies by Albert Michotte. Many cognitive and machine learning scientists believe that intelligent behavior requires agents to possess causal models of the world. Recent ML algorithms exploit the dependence structure of additive noise terms for inferring causal structures from observational data, e.g. to detect the direction of time series; the arrow of time. This raises the question whether the subtle asymmetries between the time directions can also be perceived by humans. Here we show that human observers can indeed discriminate forward and backward autoregressive motion with non-Gaussian additive independent noise, i.e. they appear sensitive to subtle asymmetries between the time directions. We employ a so-called frozen noise paradigm enabling us to compare human performance with four different algorithms on a trial-by-trial basis: A causal inference algorithm exploiting the dependence structure of additive noise terms, a neurally inspired network, a Bayesian ideal observer model as well as a simple heuristic. Our results suggest that all human observers use similar cues or strategies to solve the arrow of time motion discrimination task, but the human algorithm is significantly different from the three machine algorithms we compared it to. In fact, our simple heuristic appears most similar to our human observers. |
| Tasks | Causal Inference, Time Series |
| Published | 2019-12-01 |
| URL | http://papers.nips.cc/paper/8502-perceiving-the-arrow-of-time-in-autoregressive-motion |
| http://papers.nips.cc/paper/8502-perceiving-the-arrow-of-time-in-autoregressive-motion.pdf | |
| PWC | https://paperswithcode.com/paper/perceiving-the-arrow-of-time-in |
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Modeling the Acquisition of Words with Multiple Meanings
| Title | Modeling the Acquisition of Words with Multiple Meanings |
| Authors | Libby Barak, Sammy Floyd, Adele Goldberg |
| Abstract | |
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| Published | 2019-01-01 |
| URL | https://www.aclweb.org/anthology/W19-0122/ |
| https://www.aclweb.org/anthology/W19-0122 | |
| PWC | https://paperswithcode.com/paper/modeling-the-acquisition-of-words-with |
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A Quantitative Analysis of Patients’ Narratives of Heart Failure
| Title | A Quantitative Analysis of Patients’ Narratives of Heart Failure |
| Authors | Sabita Acharya, Barbara Di Eugenio, Andrew Boyd, Richard Cameron, Karen Dunn Lopez, Pamela Martyn-Nemeth, Debaleena Chattopadhyay, Pantea Habibi, Carolyn Dickens, Haleh Vatani, Amer Ardati |
| Abstract | Patients with chronic conditions like heart failure are the most likely to be re-hospitalized. One step towards avoiding re-hospitalization is to devise strategies for motivating patients to take care of their own health. In this paper, we perform a quantitative analysis of patients{'} narratives of their experience with heart failure and explore the different topics that patients talk about. We compare two different groups of patients- those unable to take charge of their illness, and those who make efforts to improve their health. We will use the findings from our analysis to refine and personalize the summaries of hospitalizations that our system automatically generates. |
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| Published | 2019-09-01 |
| URL | https://www.aclweb.org/anthology/W19-5928/ |
| https://www.aclweb.org/anthology/W19-5928 | |
| PWC | https://paperswithcode.com/paper/a-quantitative-analysis-of-patients |
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Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
| Title | Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) |
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| Published | 2019-11-01 |
| URL | https://www.aclweb.org/anthology/D19-1000/ |
| https://www.aclweb.org/anthology/D19-1000 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-2019-conference-on |
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Improving Neural Machine Translation Using Noisy Parallel Data through Distillation
| Title | Improving Neural Machine Translation Using Noisy Parallel Data through Distillation |
| Authors | Praveen Dakwale, Christof Monz |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2019-08-01 |
| URL | https://www.aclweb.org/anthology/W19-6612/ |
| https://www.aclweb.org/anthology/W19-6612 | |
| PWC | https://paperswithcode.com/paper/improving-neural-machine-translation-using |
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