paper_id stringlengths 8 8 | title stringlengths 19 134 | paper_url stringlengths 34 34 | authors listlengths 1 19 | abstract large_stringlengths 361 1.56k | anthology_id stringlengths 8 8 | doi stringlengths 20 20 | award stringclasses 3
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P19-1001 | One Time of Interaction May Not Be Enough: Go Deep with an Interaction-over-Interaction Network for Response Selection in Dialogues | https://aclanthology.org/P19-1001/ | [
"Chongyang Tao",
"Wei Wu",
"Can Xu",
"Wenpeng Hu",
"Dongyan Zhao",
"Rui Yan"
] | Currently, researchers have paid great attention to retrieval-based dialogues in open-domain. In particular, people study the problem by investigating context-response matching for multi-turn response selection based on publicly recognized benchmark data sets. State-of-the-art methods require a response to interact wit... | P19-1001 | 10.18653/v1/P19-1001 | null | null | null |
P19-1002 | Incremental Transformer with Deliberation Decoder for Document Grounded Conversations | https://aclanthology.org/P19-1002/ | [
"Zekang Li",
"Cheng Niu",
"Fandong Meng",
"Yang Feng",
"Qian Li",
"Jie Zhou"
] | Document Grounded Conversations is a task to generate dialogue responses when chatting about the content of a given document. Obviously, document knowledge plays a critical role in Document Grounded Conversations, while existing dialogue models do not exploit this kind of knowledge effectively enough. In this paper, we... | P19-1002 | 10.18653/v1/P19-1002 | null | 1907.08854 | title_snapshot |
P19-1003 | Improving Multi-turn Dialogue Modelling with Utterance ReWriter | https://aclanthology.org/P19-1003/ | [
"Hui Su",
"Xiaoyu Shen",
"Rongzhi Zhang",
"Fei Sun",
"Pengwei Hu",
"Cheng Niu",
"Jie Zhou"
] | Recent research has achieved impressive results in single-turn dialogue modelling. In the multi-turn setting, however, current models are still far from satisfactory. One major challenge is the frequently occurred coreference and information omission in our daily conversation, making it hard for machines to understand ... | P19-1003 | 10.18653/v1/P19-1003 | null | 1906.07004 | title_snapshot |
P19-1004 | Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study | https://aclanthology.org/P19-1004/ | [
"Chinnadhurai Sankar",
"Sandeep Subramanian",
"Chris Pal",
"Sarath Chandar",
"Yoshua Bengio"
] | Neural generative models have been become increasingly popular when building conversational agents. They offer flexibility, can be easily adapted to new domains, and require minimal domain engineering. A common criticism of these systems is that they seldom understand or use the available dialog history effectively. In... | P19-1004 | 10.18653/v1/P19-1004 | null | 1906.01603 | title_snapshot |
P19-1005 | Boosting Dialog Response Generation | https://aclanthology.org/P19-1005/ | [
"Wenchao Du",
"Alan W Black"
] | Neural models have become one of the most important approaches to dialog response generation. However, they still tend to generate the most common and generic responses in the corpus all the time. To address this problem, we designed an iterative training process and ensemble method based on boosting. We combined our m... | P19-1005 | 10.18653/v1/P19-1005 | null | null | null |
P19-1006 | Constructing Interpretive Spatio-Temporal Features for Multi-Turn Responses Selection | https://aclanthology.org/P19-1006/ | [
"Junyu Lu",
"Chenbin Zhang",
"Zeying Xie",
"Guang Ling",
"Tom Chao Zhou",
"Zenglin Xu"
] | Response selection plays an important role in fully automated dialogue systems. Given the dialogue context, the goal of response selection is to identify the best-matched next utterance (i.e., response) from multiple candidates. Despite the efforts of many previous useful models, this task remains challenging due to th... | P19-1006 | 10.18653/v1/P19-1006 | null | null | null |
P19-1007 | Semantic Parsing with Dual Learning | https://aclanthology.org/P19-1007/ | [
"Ruisheng Cao",
"Su Zhu",
"Chen Liu",
"Jieyu Li",
"Kai Yu"
] | Semantic parsing converts natural language queries into structured logical forms. The lack of training data is still one of the most serious problems in this area. In this work, we develop a semantic parsing framework with the dual learning algorithm, which enables a semantic parser to make full use of data (labeled an... | P19-1007 | 10.18653/v1/P19-1007 | null | 1907.05343 | title_snapshot |
P19-1008 | Semantic Expressive Capacity with Bounded Memory | https://aclanthology.org/P19-1008/ | [
"Antoine Venant",
"Alexander Koller"
] | We investigate the capacity of mechanisms for compositional semantic parsing to describe relations between sentences and semantic representations. We prove that in order to represent certain relations, mechanisms which are syntactically projective must be able to remember an unbounded number of locations in the semanti... | P19-1008 | 10.18653/v1/P19-1008 | null | 1906.11752 | title_snapshot |
P19-1009 | AMR Parsing as Sequence-to-Graph Transduction | https://aclanthology.org/P19-1009/ | [
"Sheng Zhang",
"Xutai Ma",
"Kevin Duh",
"Benjamin Van Durme"
] | We propose an attention-based model that treats AMR parsing as sequence-to-graph transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic resources, or data augmentation, our proposed parser is aligner-free, and it can be effectively trained with limited amounts of labeled AMR data. Ou... | P19-1009 | 10.18653/v1/P19-1009 | null | 1905.08704 | title_snapshot |
P19-1010 | Generating Logical Forms from Graph Representations of Text and Entities | https://aclanthology.org/P19-1010/ | [
"Peter Shaw",
"Philip Massey",
"Angelica Chen",
"Francesco Piccinno",
"Yasemin Altun"
] | Structured information about entities is critical for many semantic parsing tasks. We present an approach that uses a Graph Neural Network (GNN) architecture to incorporate information about relevant entities and their relations during parsing. Combined with a decoder copy mechanism, this approach provides a conceptual... | P19-1010 | 10.18653/v1/P19-1010 | null | 1905.08407 | title_snapshot |
P19-1011 | Learning Compressed Sentence Representations for On-Device Text Processing | https://aclanthology.org/P19-1011/ | [
"Dinghan Shen",
"Pengyu Cheng",
"Dhanasekar Sundararaman",
"Xinyuan Zhang",
"Qian Yang",
"Meng Tang",
"Asli Celikyilmaz",
"Lawrence Carin"
] | Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems. The learned representations are generally assumed to be continuous and real-valued, giving rise to a large memory footprint and slow retrieval speed, which hinders their... | P19-1011 | 10.18653/v1/P19-1011 | null | 1906.08340 | title_snapshot |
P19-1012 | The (Non-)Utility of Structural Features in BiLSTM-based Dependency Parsers | https://aclanthology.org/P19-1012/ | [
"Agnieszka Falenska",
"Jonas Kuhn"
] | Classical non-neural dependency parsers put considerable effort on the design of feature functions. Especially, they benefit from information coming from structural features, such as features drawn from neighboring tokens in the dependency tree. In contrast, their BiLSTM-based successors achieve state-of-the-art perfor... | P19-1012 | 10.18653/v1/P19-1012 | null | 1905.12676 | title_snapshot |
P19-1013 | Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation | https://aclanthology.org/P19-1013/ | [
"Masashi Yoshikawa",
"Hiroshi Noji",
"Koji Mineshima",
"Daisuke Bekki"
] | We propose a new domain adaptation method for Combinatory Categorial Grammar (CCG) parsing, based on the idea of automatic generation of CCG corpora exploiting cheaper resources of dependency trees. Our solution is conceptually simple, and not relying on a specific parser architecture, making it applicable to the curre... | P19-1013 | 10.18653/v1/P19-1013 | null | 1906.01834 | title_snapshot |
P19-1014 | A Joint Named-Entity Recognizer for Heterogeneous Tag-sets Using a Tag Hierarchy | https://aclanthology.org/P19-1014/ | [
"Genady Beryozkin",
"Yoel Drori",
"Oren Gilon",
"Tzvika Hartman",
"Idan Szpektor"
] | We study a variant of domain adaptation for named-entity recognition where multiple, heterogeneously tagged training sets are available. Furthermore, the test tag-set is not identical to any individual training tag-set. Yet, the relations between all tags are provided in a tag hierarchy, covering the test tags as a com... | P19-1014 | 10.18653/v1/P19-1014 | null | 1905.09135 | title_snapshot |
P19-1015 | Massively Multilingual Transfer for NER | https://aclanthology.org/P19-1015/ | [
"Afshin Rahimi",
"Yuan Li",
"Trevor Cohn"
] | In cross-lingual transfer, NLP models over one or more source languages are applied to a low-resource target language. While most prior work has used a single source model or a few carefully selected models, here we consider a “massive” setting with many such models. This setting raises the problem of poor transfer, pa... | P19-1015 | 10.18653/v1/P19-1015 | null | 1902.00193 | title_snapshot |
P19-1016 | Reliability-aware Dynamic Feature Composition for Name Tagging | https://aclanthology.org/P19-1016/ | [
"Ying Lin",
"Liyuan Liu",
"Heng Ji",
"Dong Yu",
"Jiawei Han"
] | Word embeddings are widely used on a variety of tasks and can substantially improve the performance. However, their quality is not consistent throughout the vocabulary due to the long-tail distribution of word frequency. Without sufficient contexts, rare word embeddings are usually less reliable than those of common wo... | P19-1016 | 10.18653/v1/P19-1016 | null | null | null |
P19-1017 | Unsupervised Pivot Translation for Distant Languages | https://aclanthology.org/P19-1017/ | [
"Yichong Leng",
"Xu Tan",
"Tao Qin",
"Xiang-Yang Li",
"Tie-Yan Liu"
] | Unsupervised neural machine translation (NMT) has attracted a lot of attention recently. While state-of-the-art methods for unsupervised translation usually perform well between similar languages (e.g., English-German translation), they perform poorly between distant languages, because unsupervised alignment does not w... | P19-1017 | 10.18653/v1/P19-1017 | null | 1906.02461 | title_snapshot |
P19-1018 | Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces | https://aclanthology.org/P19-1018/ | [
"Barun Patra",
"Joel Ruben Antony Moniz",
"Sarthak Garg",
"Matthew R. Gormley",
"Graham Neubig"
] | Recent work on bilingual lexicon induction (BLI) has frequently depended either on aligned bilingual lexicons or on distribution matching, often with an assumption about the isometry of the two spaces. We propose a technique to quantitatively estimate this assumption of the isometry between two embedding spaces and emp... | P19-1018 | 10.18653/v1/P19-1018 | null | 1908.06625 | title_snapshot |
P19-1019 | An Effective Approach to Unsupervised Machine Translation | https://aclanthology.org/P19-1019/ | [
"Mikel Artetxe",
"Gorka Labaka",
"Eneko Agirre"
] | While machine translation has traditionally relied on large amounts of parallel corpora, a recent research line has managed to train both Neural Machine Translation (NMT) and Statistical Machine Translation (SMT) systems using monolingual corpora only. In this paper, we identify and address several deficiencies of exis... | P19-1019 | 10.18653/v1/P19-1019 | null | 1902.01313 | title_snapshot |
P19-1020 | Effective Adversarial Regularization for Neural Machine Translation | https://aclanthology.org/P19-1020/ | [
"Motoki Sato",
"Jun Suzuki",
"Shun Kiyono"
] | A regularization technique based on adversarial perturbation, which was initially developed in the field of image processing, has been successfully applied to text classification tasks and has yielded attractive improvements. We aim to further leverage this promising methodology into more sophisticated and critical neu... | P19-1020 | 10.18653/v1/P19-1020 | null | null | null |
P19-1021 | Revisiting Low-Resource Neural Machine Translation: A Case Study | https://aclanthology.org/P19-1021/ | [
"Rico Sennrich",
"Biao Zhang"
] | It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of auxiliary data to achieve competitive results. In this paper, we re-assess the validity of these result... | P19-1021 | 10.18653/v1/P19-1021 | null | 1905.11901 | title_snapshot |
P19-1022 | Domain Adaptive Inference for Neural Machine Translation | https://aclanthology.org/P19-1022/ | [
"Danielle Saunders",
"Felix Stahlberg",
"Adrià de Gispert",
"Bill Byrne"
] | We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing performance on the original domain. We adapt sequentially across two Spanish-English and three English-German tasks, comparing unregularized... | P19-1022 | 10.18653/v1/P19-1022 | null | 1906.00408 | title_snapshot |
P19-1023 | Neural Relation Extraction for Knowledge Base Enrichment | https://aclanthology.org/P19-1023/ | [
"Bayu Distiawan Trisedya",
"Gerhard Weikum",
"Jianzhong Qi",
"Rui Zhang"
] | We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an existing KB in an end-to-end manner. Previous studies focus on the extraction itself and rely on Nam... | P19-1023 | 10.18653/v1/P19-1023 | null | null | null |
P19-1024 | Attention Guided Graph Convolutional Networks for Relation Extraction | https://aclanthology.org/P19-1024/ | [
"Zhijiang Guo",
"Yan Zhang",
"Wei Lu"
] | Dependency trees convey rich structural information that is proven useful for extracting relations among entities in text. However, how to effectively make use of relevant information while ignoring irrelevant information from the dependency trees remains a challenging research question. Existing approaches employing r... | P19-1024 | 10.18653/v1/P19-1024 | null | 1906.07510 | title_snapshot |
P19-1025 | Spatial Aggregation Facilitates Discovery of Spatial Topics | https://aclanthology.org/P19-1025/ | [
"Aniruddha Maiti",
"Slobodan Vucetic"
] | Spatial aggregation refers to merging of documents created at the same spatial location. We show that by spatial aggregation of a large collection of documents and applying a traditional topic discovery algorithm on the aggregated data we can efficiently discover spatially distinct topics. By looking at topic discovery... | P19-1025 | 10.18653/v1/P19-1025 | null | null | null |
P19-1026 | Relation Embedding with Dihedral Group in Knowledge Graph | https://aclanthology.org/P19-1026/ | [
"Canran Xu",
"Ruijiang Li"
] | Link prediction is critical for the application of incomplete knowledge graph (KG) in the downstream tasks. As a family of effective approaches for link predictions, embedding methods try to learn low-rank representations for both entities and relations such that the bilinear form defined therein is a well-behaved scor... | P19-1026 | 10.18653/v1/P19-1026 | null | 1906.00687 | title_snapshot |
P19-1027 | Sequence Tagging with Contextual and Non-Contextual Subword Representations: A Multilingual Evaluation | https://aclanthology.org/P19-1027/ | [
"Benjamin Heinzerling",
"Michael Strube"
] | Pretrained contextual and non-contextual subword embeddings have become available in over 250 languages, allowing massively multilingual NLP. However, while there is no dearth of pretrained embeddings, the distinct lack of systematic evaluations makes it difficult for practitioners to choose between them. In this work,... | P19-1027 | 10.18653/v1/P19-1027 | null | 1906.01569 | title_snapshot |
P19-1028 | Augmenting Neural Networks with First-order Logic | https://aclanthology.org/P19-1028/ | [
"Tao Li",
"Vivek Srikumar"
] | Today, the dominant paradigm for training neural networks involves minimizing task loss on a large dataset. Using world knowledge to inform a model, and yet retain the ability to perform end-to-end training remains an open question. In this paper, we present a novel framework for introducing declarative knowledge to ne... | P19-1028 | 10.18653/v1/P19-1028 | null | 1906.06298 | title_snapshot |
P19-1029 | Self-Regulated Interactive Sequence-to-Sequence Learning | https://aclanthology.org/P19-1029/ | [
"Julia Kreutzer",
"Stefan Riezler"
] | Not all types of supervision signals are created equal: Different types of feedback have different costs and effects on learning. We show how self-regulation strategies that decide when to ask for which kind of feedback from a teacher (or from oneself) can be cast as a learning-to-learn problem leading to improved cost... | P19-1029 | 10.18653/v1/P19-1029 | null | 1907.05190 | title_snapshot |
P19-1030 | You Only Need Attention to Traverse Trees | https://aclanthology.org/P19-1030/ | [
"Mahtab Ahmed",
"Muhammad Rifayat Samee",
"Robert E. Mercer"
] | In recent NLP research, a topic of interest is universal sentence encoding, sentence representations that can be used in any supervised task. At the word sequence level, fully attention-based models suffer from two problems: a quadratic increase in memory consumption with respect to the sentence length and an inability... | P19-1030 | 10.18653/v1/P19-1030 | null | null | null |
P19-1031 | Cross-Domain Generalization of Neural Constituency Parsers | https://aclanthology.org/P19-1031/ | [
"Daniel Fried",
"Nikita Kitaev",
"Dan Klein"
] | Neural parsers obtain state-of-the-art results on benchmark treebanks for constituency parsing—but to what degree do they generalize to other domains? We present three results about the generalization of neural parsers in a zero-shot setting: training on trees from one corpus and evaluating on out-of-domain corpora. Fi... | P19-1031 | 10.18653/v1/P19-1031 | null | 1907.04347 | title_snapshot |
P19-1032 | Adaptive Attention Span in Transformers | https://aclanthology.org/P19-1032/ | [
"Sainbayar Sukhbaatar",
"Edouard Grave",
"Piotr Bojanowski",
"Armand Joulin"
] | We propose a novel self-attention mechanism that can learn its optimal attention span. This allows us to extend significantly the maximum context size used in Transformer, while maintaining control over their memory footprint and computational time. We show the effectiveness of our approach on the task of character lev... | P19-1032 | 10.18653/v1/P19-1032 | null | 1905.07799 | title_snapshot |
P19-1033 | Neural News Recommendation with Long- and Short-term User Representations | https://aclanthology.org/P19-1033/ | [
"Mingxiao An",
"Fangzhao Wu",
"Chuhan Wu",
"Kun Zhang",
"Zheng Liu",
"Xing Xie"
] | Personalized news recommendation is important to help users find their interested news and improve reading experience. A key problem in news recommendation is learning accurate user representations to capture their interests. Users usually have both long-term preferences and short-term interests. However, existing news... | P19-1033 | 10.18653/v1/P19-1033 | null | null | null |
P19-1034 | Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes | https://aclanthology.org/P19-1034/ | [
"Marina Sedinkina",
"Nikolas Breitkopf",
"Hinrich Schütze"
] | In this paper, we automatically create sentiment dictionaries for predicting financial outcomes. We compare three approaches: (i) manual adaptation of the domain-general dictionary H4N, (ii) automatic adaptation of H4N and (iii) a combination consisting of first manual, then automatic adaptation. In our experiments, we... | P19-1034 | 10.18653/v1/P19-1034 | null | 2006.14209 | title_snapshot |
P19-1035 | Manipulating the Difficulty of C-Tests | https://aclanthology.org/P19-1035/ | [
"Ji-Ung Lee",
"Erik Schwan",
"Christian M. Meyer"
] | We propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically. This is a crucial step towards generating learner-adaptive exercises for self-directed language learning and preparing language assessment tests. To reach the desired difficulty level, we manipulate the s... | P19-1035 | 10.18653/v1/P19-1035 | null | 1906.06905 | title_snapshot |
P19-1036 | Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings | https://aclanthology.org/P19-1036/ | [
"Zied Haj-Yahia",
"Adrien Sieg",
"Léa A. Deleris"
] | Text classification aims at mapping documents into a set of predefined categories. Supervised machine learning models have shown great success in this area but they require a large number of labeled documents to reach adequate accuracy. This is particularly true when the number of target categories is in the tens or th... | P19-1036 | 10.18653/v1/P19-1036 | null | null | null |
P19-1037 | Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table | https://aclanthology.org/P19-1037/ | [
"Matthew Shardlow",
"Raheel Nawaz"
] | Clinical letters are infamously impenetrable for the lay patient. This work uses neural text simplification methods to automatically improve the understandability of clinical letters for patients. We take existing neural text simplification software and augment it with a new phrase table that links complex medical term... | P19-1037 | 10.18653/v1/P19-1037 | null | null | null |
P19-1038 | What You Say and How You Say It Matters: Predicting Stock Volatility Using Verbal and Vocal Cues | https://aclanthology.org/P19-1038/ | [
"Yu Qin",
"Yi Yang"
] | Predicting financial risk is an essential task in financial market. Prior research has shown that textual information in a firm’s financial statement can be used to predict its stock’s risk level. Nowadays, firm CEOs communicate information not only verbally through press releases and financial reports, but also nonver... | P19-1038 | 10.18653/v1/P19-1038 | null | null | null |
P19-1039 | Detecting Concealed Information in Text and Speech | https://aclanthology.org/P19-1039/ | [
"Shengli Hu"
] | Motivated by infamous cheating scandals in the media industry, the wine industry, and political campaigns, we address the problem of detecting concealed information in technical settings. In this work, we explore acoustic-prosodic and linguistic indicators of information concealment by collecting a unique corpus of pro... | P19-1039 | 10.18653/v1/P19-1039 | null | null | null |
P19-1040 | Evidence-based Trustworthiness | https://aclanthology.org/P19-1040/ | [
"Yi Zhang",
"Zachary Ives",
"Dan Roth"
] | The information revolution brought with it information pollution. Information retrieval and extraction help us cope with abundant information from diverse sources. But some sources are of anonymous authorship, and some are of uncertain accuracy, so how can we determine what we should actually believe? Not all informati... | P19-1040 | 10.18653/v1/P19-1040 | null | null | null |
P19-1041 | Disentangled Representation Learning for Non-Parallel Text Style Transfer | https://aclanthology.org/P19-1041/ | [
"Vineet John",
"Lili Mou",
"Hareesh Bahuleyan",
"Olga Vechtomova"
] | This paper tackles the problem of disentangling the latent representations of style and content in language models. We propose a simple yet effective approach, which incorporates auxiliary multi-task and adversarial objectives, for style prediction and bag-of-words prediction, respectively. We show, both qualitatively ... | P19-1041 | 10.18653/v1/P19-1041 | null | 1808.04339 | title_snapshot |
P19-1042 | Cross-Sentence Grammatical Error Correction | https://aclanthology.org/P19-1042/ | [
"Shamil Chollampatt",
"Weiqi Wang",
"Hwee Tou Ng"
] | Automatic grammatical error correction (GEC) research has made remarkable progress in the past decade. However, all existing approaches to GEC correct errors by considering a single sentence alone and ignoring crucial cross-sentence context. Some errors can only be corrected reliably using cross-sentence context and mo... | P19-1042 | 10.18653/v1/P19-1042 | null | null | null |
P19-1043 | This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation | https://aclanthology.org/P19-1043/ | [
"Rui Zhang",
"Joel Tetreault"
] | Given the overwhelming number of emails, an effective subject line becomes essential to better inform the recipient of the email’s content. In this paper, we propose and study the task of email subject line generation: automatically generating an email subject line from the email body. We create the first dataset for t... | P19-1043 | 10.18653/v1/P19-1043 | null | 1906.03497 | title_snapshot |
P19-1044 | Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change | https://aclanthology.org/P19-1044/ | [
"Haim Dubossarsky",
"Simon Hengchen",
"Nina Tahmasebi",
"Dominik Schlechtweg"
] | State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have empirically tested the Temporal Referencing method for lexical semantic change and show that, by avoiding alignment, it is less affected by this noise. We show that, trained on a diachronic corpu... | P19-1044 | 10.18653/v1/P19-1044 | null | 1906.01688 | title_snapshot |
P19-1045 | Adversarial Attention Modeling for Multi-dimensional Emotion Regression | https://aclanthology.org/P19-1045/ | [
"Suyang Zhu",
"Shoushan Li",
"Guodong Zhou"
] | In this paper, we propose a neural network-based approach, namely Adversarial Attention Network, to the task of multi-dimensional emotion regression, which automatically rates multiple emotion dimension scores for an input text. Especially, to determine which words are valuable for a particular emotion dimension, an at... | P19-1045 | 10.18653/v1/P19-1045 | null | null | null |
P19-1046 | Divide, Conquer and Combine: Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing | https://aclanthology.org/P19-1046/ | [
"Sijie Mai",
"Haifeng Hu",
"Songlong Xing"
] | We propose a general strategy named ‘divide, conquer and combine’ for multimodal fusion. Instead of directly fusing features at holistic level, we conduct fusion hierarchically so that both local and global interactions are considered for a comprehensive interpretation of multimodal embeddings. In the ‘divide’ and ‘con... | P19-1046 | 10.18653/v1/P19-1046 | null | null | null |
P19-1047 | Modeling Financial Analysts’ Decision Making via the Pragmatics and Semantics of Earnings Calls | https://aclanthology.org/P19-1047/ | [
"Katherine A. Keith",
"Amanda Stent"
] | Every fiscal quarter, companies hold earnings calls in which company executives respond to questions from analysts. After these calls, analysts often change their price target recommendations, which are used in equity re- search reports to help investors make deci- sions. In this paper, we examine analysts’ decision ma... | P19-1047 | 10.18653/v1/P19-1047 | null | 1906.02868 | title_snapshot |
P19-1048 | An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis | https://aclanthology.org/P19-1048/ | [
"Ruidan He",
"Wee Sun Lee",
"Hwee Tou Ng",
"Daniel Dahlmeier"
] | Aspect-based sentiment analysis produces a list of aspect terms and their corresponding sentiments for a natural language sentence. This task is usually done in a pipeline manner, with aspect term extraction performed first, followed by sentiment predictions toward the extracted aspect terms. While easier to develop, s... | P19-1048 | 10.18653/v1/P19-1048 | null | 1906.06906 | title_snapshot |
P19-1049 | Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction | https://aclanthology.org/P19-1049/ | [
"Debela Gemechu",
"Chris Reed"
] | This work presents an approach decomposing propositions into four functional components and identify the patterns linking those components to determine argument structure. The entities addressed by a proposition are target concepts and the features selected to make a point about the target concepts are aspects. A line ... | P19-1049 | 10.18653/v1/P19-1049 | null | null | null |
P19-1050 | MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations | https://aclanthology.org/P19-1050/ | [
"Soujanya Poria",
"Devamanyu Hazarika",
"Navonil Majumder",
"Gautam Naik",
"Erik Cambria",
"Rada Mihalcea"
] | Emotion recognition in conversations is a challenging task that has recently gained popularity due to its potential applications. Until now, however, a large-scale multimodal multi-party emotional conversational database containing more than two speakers per dialogue was missing. Thus, we propose the Multimodal Emotion... | P19-1050 | 10.18653/v1/P19-1050 | null | 1810.02508 | title_snapshot |
P19-1051 | Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification | https://aclanthology.org/P19-1051/ | [
"Minghao Hu",
"Yuxing Peng",
"Zhen Huang",
"Dongsheng Li",
"Yiwei Lv"
] | Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence. Prior work typically formulates this task as a sequence tagging problem. However, such formulation suffers from problems such as huge search space and sentiment inconsistency. To address these p... | P19-1051 | 10.18653/v1/P19-1051 | null | 1906.03820 | title_snapshot |
P19-1052 | Transfer Capsule Network for Aspect Level Sentiment Classification | https://aclanthology.org/P19-1052/ | [
"Zhuang Chen",
"Tieyun Qian"
] | Aspect-level sentiment classification aims to determine the sentiment polarity of a sentence towards an aspect. Due to the high cost in annotation, the lack of aspect-level labeled data becomes a major obstacle in this area. On the other hand, document-level labeled data like reviews are easily accessible from online w... | P19-1052 | 10.18653/v1/P19-1052 | null | null | null |
P19-1053 | Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis | https://aclanthology.org/P19-1053/ | [
"Jialong Tang",
"Ziyao Lu",
"Jinsong Su",
"Yubin Ge",
"Linfeng Song",
"Le Sun",
"Jiebo Luo"
] | In aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given aspect. However, such a mechanism tends to excessively focus on a few frequent words with sentiment polarities, while igno... | P19-1053 | 10.18653/v1/P19-1053 | null | 1906.01213 | title_snapshot |
P19-1054 | Classification and Clustering of Arguments with Contextualized Word Embeddings | https://aclanthology.org/P19-1054/ | [
"Nils Reimers",
"Benjamin Schiller",
"Tilman Beck",
"Johannes Daxenberger",
"Christian Stab",
"Iryna Gurevych"
] | We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search. For the first time, we show how to leverage the power of contextualized word embeddings to classify and cluster topic-dependent arguments, achieving impressive results on both tasks and acr... | P19-1054 | 10.18653/v1/P19-1054 | null | 1906.09821 | title_snapshot |
P19-1055 | Sentiment Tagging with Partial Labels using Modular Architectures | https://aclanthology.org/P19-1055/ | [
"Xiao Zhang",
"Dan Goldwasser"
] | Many NLP learning tasks can be decomposed into several distinct sub-tasks, each associated with a partial label. In this paper we focus on a popular class of learning problems, sequence prediction applied to several sentiment analysis tasks, and suggest a modular learning approach in which different sub-tasks are learn... | P19-1055 | 10.18653/v1/P19-1055 | null | 1906.00534 | title_snapshot |
P19-1056 | DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction | https://aclanthology.org/P19-1056/ | [
"Huaishao Luo",
"Tianrui Li",
"Bing Liu",
"Junbo Zhang"
] | This paper focuses on two related subtasks of aspect-based sentiment analysis, namely aspect term extraction and aspect sentiment classification, which we call aspect term-polarity co-extraction. The former task is to extract aspects of a product or service from an opinion document, and the latter is to identify the po... | P19-1056 | 10.18653/v1/P19-1056 | null | 1906.01794 | title_snapshot |
P19-1057 | A Corpus for Modeling User and Language Effects in Argumentation on Online Debating | https://aclanthology.org/P19-1057/ | [
"Esin Durmus",
"Claire Cardie"
] | Existing argumentation datasets have succeeded in allowing researchers to develop computational methods for analyzing the content, structure and linguistic features of argumentative text. They have been much less successful in fostering studies of the effect of “user” traits — characteristics and beliefs of the partici... | P19-1057 | 10.18653/v1/P19-1057 | null | 1906.11310 | title_snapshot |
P19-1058 | Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese | https://aclanthology.org/P19-1058/ | [
"Sheng Xu",
"Peifeng Li",
"Fang Kong",
"Qiaoming Zhu",
"Guodong Zhou"
] | In the literature, most of the previous studies on English implicit discourse relation recognition only use sentence-level representations, which cannot provide enough semantic information in Chinese due to its unique paratactic characteristics. In this paper, we propose a topic tensor network to recognize Chinese impl... | P19-1058 | 10.18653/v1/P19-1058 | null | null | null |
P19-1059 | Learning from Omission | https://aclanthology.org/P19-1059/ | [
"Bill McDowell",
"Noah Goodman"
] | Pragmatic reasoning allows humans to go beyond the literal meaning when interpret- ing language in context. Previous work has shown that such reasoning can improve the performance of already-trained language understanding systems. Here, we explore whether pragmatic reasoning during training can improve the quality of l... | P19-1059 | 10.18653/v1/P19-1059 | null | null | null |
P19-1060 | Multi-Task Learning for Coherence Modeling | https://aclanthology.org/P19-1060/ | [
"Youmna Farag",
"Helen Yannakoudakis"
] | We address the task of assessing discourse coherence, an aspect of text quality that is essential for many NLP tasks, such as summarization and language assessment. We propose a hierarchical neural network trained in a multi-task fashion that learns to predict a document-level coherence score (at the network’s top laye... | P19-1060 | 10.18653/v1/P19-1060 | null | 1907.02427 | title_snapshot |
P19-1061 | Data Programming for Learning Discourse Structure | https://aclanthology.org/P19-1061/ | [
"Sonia Badene",
"Kate Thompson",
"Jean-Pierre Lorré",
"Nicholas Asher"
] | This paper investigates the advantages and limits of data programming for the task of learning discourse structure. The data programming paradigm implemented in the Snorkel framework allows a user to label training data using expert-composed heuristics, which are then transformed via the “generative step” into probabil... | P19-1061 | 10.18653/v1/P19-1061 | null | null | null |
P19-1062 | Evaluating Discourse in Structured Text Representations | https://aclanthology.org/P19-1062/ | [
"Elisa Ferracane",
"Greg Durrett",
"Junyi Jessy Li",
"Katrin Erk"
] | Discourse structure is integral to understanding a text and is helpful in many NLP tasks. Learning latent representations of discourse is an attractive alternative to acquiring expensive labeled discourse data. Liu and Lapata (2018) propose a structured attention mechanism for text classification that derives a tree ov... | P19-1062 | 10.18653/v1/P19-1062 | null | 1906.01472 | title_snapshot |
P19-1063 | Know What You Don’t Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories | https://aclanthology.org/P19-1063/ | [
"Sina Zarrieß",
"David Schlangen"
] | Zero-shot learning in Language & Vision is the task of correctly labelling (or naming) objects of novel categories. Another strand of work in L&V aims at pragmatically informative rather than “correct” object descriptions, e.g. in reference games. We combine these lines of research and model zero-shot reference games, ... | P19-1063 | 10.18653/v1/P19-1063 | null | 1906.05518 | title_snapshot |
P19-1064 | End-to-end Deep Reinforcement Learning Based Coreference Resolution | https://aclanthology.org/P19-1064/ | [
"Hongliang Fei",
"Xu Li",
"Dingcheng Li",
"Ping Li"
] | Recent neural network models have significantly advanced the task of coreference resolution. However, current neural coreference models are usually trained with heuristic loss functions that are computed over a sequence of local decisions. In this paper, we introduce an end-to-end reinforcement learning based coreferen... | P19-1064 | 10.18653/v1/P19-1064 | null | null | null |
P19-1065 | Implicit Discourse Relation Identification for Open-domain Dialogues | https://aclanthology.org/P19-1065/ | [
"Mingyu Derek Ma",
"Kevin Bowden",
"Jiaqi Wu",
"Wen Cui",
"Marilyn Walker"
] | Discourse relation identification has been an active area of research for many years, and the challenge of identifying implicit relations remains largely an unsolved task, especially in the context of an open-domain dialogue system. Previous work primarily relies on a corpora of formal text which is inherently non-dial... | P19-1065 | 10.18653/v1/P19-1065 | null | 1907.03975 | title_snapshot |
P19-1066 | Coreference Resolution with Entity Equalization | https://aclanthology.org/P19-1066/ | [
"Ben Kantor",
"Amir Globerson"
] | A key challenge in coreference resolution is to capture properties of entity clusters, and use those in the resolution process. Here we provide a simple and effective approach for achieving this, via an “Entity Equalization” mechanism. The Equalization approach represents each mention in a cluster via an approximation ... | P19-1066 | 10.18653/v1/P19-1066 | null | null | null |
P19-1067 | A Cross-Domain Transferable Neural Coherence Model | https://aclanthology.org/P19-1067/ | [
"Peng Xu",
"Hamidreza Saghir",
"Jin Sung Kang",
"Teng Long",
"Avishek Joey Bose",
"Yanshuai Cao",
"Jackie Chi Kit Cheung"
] | Coherence is an important aspect of text quality and is crucial for ensuring its readability. One important limitation of existing coherence models is that training on one domain does not easily generalize to unseen categories of text. Previous work advocates for generative models for cross-domain generalization, becau... | P19-1067 | 10.18653/v1/P19-1067 | null | 1905.11912 | title_snapshot |
P19-1068 | MOROCO: The Moldavian and Romanian Dialectal Corpus | https://aclanthology.org/P19-1068/ | [
"Andrei Butnaru",
"Radu Tudor Ionescu"
] | In this work, we introduce the MOldavian and ROmanian Dialectal COrpus (MOROCO), which is freely available for download at https://github.com/butnaruandrei/MOROCO. The corpus contains 33564 samples of text (with over 10 million tokens) collected from the news domain. The samples belong to one of the following six topic... | P19-1068 | 10.18653/v1/P19-1068 | null | 1901.06543 | title_snapshot |
P19-1069 | Just “OneSeC” for Producing Multilingual Sense-Annotated Data | https://aclanthology.org/P19-1069/ | [
"Bianca Scarlini",
"Tommaso Pasini",
"Roberto Navigli"
] | The well-known problem of knowledge acquisition is one of the biggest issues in Word Sense Disambiguation (WSD), where annotated data are still scarce in English and almost absent in other languages. In this paper we formulate the assumption of One Sense per Wikipedia Category and present OneSeC, a language-independent... | P19-1069 | 10.18653/v1/P19-1069 | null | null | null |
P19-1070 | How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions | https://aclanthology.org/P19-1070/ | [
"Goran Glavaš",
"Robert Litschko",
"Sebastian Ruder",
"Ivan Vulić"
] | Cross-lingual word embeddings (CLEs) facilitate cross-lingual transfer of NLP models. Despite their ubiquitous downstream usage, increasingly popular projection-based CLE models are almost exclusively evaluated on bilingual lexicon induction (BLI). Even the BLI evaluations vary greatly, hindering our ability to correct... | P19-1070 | 10.18653/v1/P19-1070 | null | 1902.00508 | title_snapshot |
P19-1071 | SP-10K: A Large-scale Evaluation Set for Selectional Preference Acquisition | https://aclanthology.org/P19-1071/ | [
"Hongming Zhang",
"Hantian Ding",
"Yangqiu Song"
] | Selectional Preference (SP) is a commonly observed language phenomenon and proved to be useful in many natural language processing tasks. To provide a better evaluation method for SP models, we introduce SP-10K, a large-scale evaluation set that provides human ratings for the plausibility of 10,000 SP pairs over five S... | P19-1071 | 10.18653/v1/P19-1071 | null | 1906.02123 | title_snapshot |
P19-1072 | A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains | https://aclanthology.org/P19-1072/ | [
"Dominik Schlechtweg",
"Anna Hätty",
"Marco Del Tredici",
"Sabine Schulte im Walde"
] | We perform an interdisciplinary large-scale evaluation for detecting lexical semantic divergences in a diachronic and in a synchronic task: semantic sense changes across time, and semantic sense changes across domains. Our work addresses the superficialness and lack of comparison in assessing models of diachronic lexic... | P19-1072 | 10.18653/v1/P19-1072 | null | 1906.02979 | title_snapshot |
P19-1073 | Errudite: Scalable, Reproducible, and Testable Error Analysis | https://aclanthology.org/P19-1073/ | [
"Tongshuang Wu",
"Marco Tulio Ribeiro",
"Jeffrey Heer",
"Daniel Weld"
] | Though error analysis is crucial to understanding and improving NLP models, the common practice of manual, subjective categorization of a small sample of errors can yield biased and incomplete conclusions. This paper codifies model and task agnostic principles for informative error analysis, and presents Errudite, an i... | P19-1073 | 10.18653/v1/P19-1073 | null | null | null |
P19-1074 | DocRED: A Large-Scale Document-Level Relation Extraction Dataset | https://aclanthology.org/P19-1074/ | [
"Yuan Yao",
"Deming Ye",
"Peng Li",
"Xu Han",
"Yankai Lin",
"Zhenghao Liu",
"Zhiyuan Liu",
"Lixin Huang",
"Jie Zhou",
"Maosong Sun"
] | Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs. In order to accelerate the research on document-level RE, we introduce DocRED, ... | P19-1074 | 10.18653/v1/P19-1074 | null | 1906.06127 | title_snapshot |
P19-1075 | ChID: A Large-scale Chinese IDiom Dataset for Cloze Test | https://aclanthology.org/P19-1075/ | [
"Chujie Zheng",
"Minlie Huang",
"Aixin Sun"
] | Cloze-style reading comprehension in Chinese is still limited due to the lack of various corpora. In this paper we propose a large-scale Chinese cloze test dataset ChID, which studies the comprehension of idiom, a unique language phenomenon in Chinese. In this corpus, the idioms in a passage are replaced by blank symbo... | P19-1075 | 10.18653/v1/P19-1075 | null | 1906.01265 | title_snapshot |
P19-1076 | Automatic Evaluation of Local Topic Quality | https://aclanthology.org/P19-1076/ | [
"Jeffrey Lund",
"Piper Armstrong",
"Wilson Fearn",
"Stephen Cowley",
"Courtni Byun",
"Jordan Boyd-Graber",
"Kevin Seppi"
] | Topic models are typically evaluated with respect to the global topic distributions that they generate, using metrics such as coherence, but without regard to local (token-level) topic assignments. Token-level assignments are important for downstream tasks such as classification. Even recent models, which aim to improv... | P19-1076 | 10.18653/v1/P19-1076 | null | 1905.13126 | title_snapshot |
P19-1077 | Crowdsourcing and Aggregating Nested Markable Annotations | https://aclanthology.org/P19-1077/ | [
"Chris Madge",
"Juntao Yu",
"Jon Chamberlain",
"Udo Kruschwitz",
"Silviu Paun",
"Massimo Poesio"
] | One of the key steps in language resource creation is the identification of the text segments to be annotated, or markables, which depending on the task may vary from nominal chunks for named entity resolution to (potentially nested) noun phrases in coreference resolution (or mentions) to larger text segments in text s... | P19-1077 | 10.18653/v1/P19-1077 | null | null | null |
P19-1078 | Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems | https://aclanthology.org/P19-1078/ | [
"Chien-Sheng Wu",
"Andrea Madotto",
"Ehsan Hosseini-Asl",
"Caiming Xiong",
"Richard Socher",
"Pascale Fung"
] | Over-dependence on domain ontology and lack of sharing knowledge across domains are two practical and yet less studied problems of dialogue state tracking. Existing approaches generally fall short when tracking unknown slot values during inference and often have difficulties in adapting to new domains. In this paper, w... | P19-1078 | 10.18653/v1/P19-1078 | Outstanding Paper | 1905.08743 | title_snapshot |
P19-1079 | Multi-Task Networks with Universe, Group, and Task Feature Learning | https://aclanthology.org/P19-1079/ | [
"Shiva Pentyala",
"Mengwen Liu",
"Markus Dreyer"
] | We present methods for multi-task learning that take advantage of natural groupings of related tasks. Task groups may be defined along known properties of the tasks, such as task domain or language. Such task groups represent supervised information at the inter-task level and can be encoded into the model. We investiga... | P19-1079 | 10.18653/v1/P19-1079 | null | 1907.01791 | title_snapshot |
P19-1080 | Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue | https://aclanthology.org/P19-1080/ | [
"Anusha Balakrishnan",
"Jinfeng Rao",
"Kartikeya Upasani",
"Michael White",
"Rajen Subba"
] | Generating fluent natural language responses from structured semantic representations is a critical step in task-oriented conversational systems. Avenues like the E2E NLG Challenge have encouraged the development of neural approaches, particularly sequence-to-sequence (Seq2Seq) models for this problem. The semantic rep... | P19-1080 | 10.18653/v1/P19-1080 | null | 1906.07220 | title_snapshot |
P19-1081 | OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs | https://aclanthology.org/P19-1081/ | [
"Seungwhan Moon",
"Pararth Shah",
"Anuj Kumar",
"Rajen Subba"
] | We study a conversational reasoning model that strategically traverses through a large-scale common fact knowledge graph (KG) to introduce engaging and contextually diverse entities and attributes. For this study, we collect a new Open-ended Dialog <-> KG parallel corpus called OpenDialKG, where each utterance from 15K... | P19-1081 | 10.18653/v1/P19-1081 | null | null | null |
P19-1082 | Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing | https://aclanthology.org/P19-1082/ | [
"Daya Guo",
"Duyu Tang",
"Nan Duan",
"Ming Zhou",
"Jian Yin"
] | In this paper, we present an approach to incorporate retrieved datapoints as supporting evidence for context-dependent semantic parsing, such as generating source code conditioned on the class environment. Our approach naturally combines a retrieval model and a meta-learner, where the former learns to find similar data... | P19-1082 | 10.18653/v1/P19-1082 | null | 1906.07108 | title_snapshot |
P19-1083 | Knowledge-aware Pronoun Coreference Resolution | https://aclanthology.org/P19-1083/ | [
"Hongming Zhang",
"Yan Song",
"Yangqiu Song",
"Dong Yu"
] | Resolving pronoun coreference requires knowledge support, especially for particular domains (e.g., medicine). In this paper, we explore how to leverage different types of knowledge to better resolve pronoun coreference with a neural model. To ensure the generalization ability of our model, we directly incorporate knowl... | P19-1083 | 10.18653/v1/P19-1083 | null | 1907.03663 | title_snapshot |
P19-1084 | Don’t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference | https://aclanthology.org/P19-1084/ | [
"Yonatan Belinkov",
"Adam Poliak",
"Stuart Shieber",
"Benjamin Van Durme",
"Alexander Rush"
] | Natural Language Inference (NLI) datasets often contain hypothesis-only biases—artifacts that allow models to achieve non-trivial performance without learning whether a premise entails a hypothesis. We propose two probabilistic methods to build models that are more robust to such biases and better transfer across datas... | P19-1084 | 10.18653/v1/P19-1084 | null | 1907.04380 | title_snapshot |
P19-1085 | GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification | https://aclanthology.org/P19-1085/ | [
"Jie Zhou",
"Xu Han",
"Cheng Yang",
"Zhiyuan Liu",
"Lifeng Wang",
"Changcheng Li",
"Maosong Sun"
] | Fact verification (FV) is a challenging task which requires to retrieve relevant evidence from plain text and use the evidence to verify given claims. Many claims require to simultaneously integrate and reason over several pieces of evidence for verification. However, previous work employs simple models to extract info... | P19-1085 | 10.18653/v1/P19-1085 | null | 1908.01843 | title_snapshot |
P19-1086 | SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference | https://aclanthology.org/P19-1086/ | [
"Martin Schmitt",
"Hinrich Schütze"
] | We present SherLIiC, a testbed for lexical inference in context (LIiC), consisting of 3985 manually annotated inference rule candidates (InfCands), accompanied by (i) ~960k unlabeled InfCands, and (ii) ~190k typed textual relations between Freebase entities extracted from the large entity-linked corpus ClueWeb09. Each ... | P19-1086 | 10.18653/v1/P19-1086 | null | 1906.01393 | title_snapshot |
P19-1087 | Extracting Symptoms and their Status from Clinical Conversations | https://aclanthology.org/P19-1087/ | [
"Nan Du",
"Kai Chen",
"Anjuli Kannan",
"Linh Tran",
"Yuhui Chen",
"Izhak Shafran"
] | This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status. Lack of any publicly available corpus in this privacy-sensitive domain led us to develop our own corpus, consisting of about 3K conversations annotated by profes... | P19-1087 | 10.18653/v1/P19-1087 | null | 1906.02239 | title_snapshot |
P19-1088 | What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations | https://aclanthology.org/P19-1088/ | [
"Verónica Pérez-Rosas",
"Xinyi Wu",
"Kenneth Resnicow",
"Rada Mihalcea"
] | The quality of a counseling intervention relies highly on the active collaboration between clients and counselors. In this paper, we explore several linguistic aspects of the collaboration process occurring during counseling conversations. Specifically, we address the differences between high-quality and low-quality co... | P19-1088 | 10.18653/v1/P19-1088 | null | null | null |
P19-1089 | Finding Your Voice: The Linguistic Development of Mental Health Counselors | https://aclanthology.org/P19-1089/ | [
"Justine Zhang",
"Robert Filbin",
"Christine Morrison",
"Jaclyn Weiser",
"Cristian Danescu-Niculescu-Mizil"
] | Mental health counseling is an enterprise with profound societal importance where conversations play a primary role. In order to acquire the conversational skills needed to face a challenging range of situations, mental health counselors must rely on training and on continued experience with actual clients. However, in... | P19-1089 | 10.18653/v1/P19-1089 | null | 1906.07194 | title_snapshot |
P19-1090 | Towards Automating Healthcare Question Answering in a Noisy Multilingual Low-Resource Setting | https://aclanthology.org/P19-1090/ | [
"Jeanne E. Daniel",
"Willie Brink",
"Ryan Eloff",
"Charles Copley"
] | We discuss ongoing work into automating a multilingual digital helpdesk service available via text messaging to pregnant and breastfeeding mothers in South Africa. Our anonymized dataset consists of short informal questions, often in low-resource languages, with unreliable language labels, spelling errors and code-mixi... | P19-1090 | 10.18653/v1/P19-1090 | null | null | null |
P19-1091 | Joint Entity Extraction and Assertion Detection for Clinical Text | https://aclanthology.org/P19-1091/ | [
"Parminder Bhatia",
"Busra Celikkaya",
"Mohammed Khalilia"
] | Negative medical findings are prevalent in clinical reports, yet discriminating them from positive findings remains a challenging task for in-formation extraction. Most of the existing systems treat this task as a pipeline of two separate tasks, i.e., named entity recognition (NER)and rule-based negation detection. We ... | P19-1091 | 10.18653/v1/P19-1091 | null | 1812.05270 | title_snapshot |
P19-1092 | HEAD-QA: A Healthcare Dataset for Complex Reasoning | https://aclanthology.org/P19-1092/ | [
"David Vilares",
"Carlos Gómez-Rodríguez"
] | We present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and are challenging even for highly specialized humans. We then consider monolingual (Spanish) and cross-lingual (to ... | P19-1092 | 10.18653/v1/P19-1092 | null | 1906.04701 | title_snapshot |
P19-1093 | Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network | https://aclanthology.org/P19-1093/ | [
"Martin Gleize",
"Eyal Shnarch",
"Leshem Choshen",
"Lena Dankin",
"Guy Moshkowich",
"Ranit Aharonov",
"Noam Slonim"
] | With the advancement in argument detection, we suggest to pay more attention to the challenging task of identifying the more convincing arguments. Machines capable of responding and interacting with humans in helpful ways have become ubiquitous. We now expect them to discuss with us the more delicate questions in our w... | P19-1093 | 10.18653/v1/P19-1093 | null | 1907.08971 | title_snapshot |
P19-1094 | From Surrogacy to Adoption; From Bitcoin to Cryptocurrency: Debate Topic Expansion | https://aclanthology.org/P19-1094/ | [
"Roy Bar-Haim",
"Dalia Krieger",
"Orith Toledo-Ronen",
"Lilach Edelstein",
"Yonatan Bilu",
"Alon Halfon",
"Yoav Katz",
"Amir Menczel",
"Ranit Aharonov",
"Noam Slonim"
] | When debating a controversial topic, it is often desirable to expand the boundaries of discussion. For example, we may consider the pros and cons of possible alternatives to the debate topic, make generalizations, or give specific examples. We introduce the task of Debate Topic Expansion - finding such related topics f... | P19-1094 | 10.18653/v1/P19-1094 | null | null | null |
P19-1095 | Multimodal and Multi-view Models for Emotion Recognition | https://aclanthology.org/P19-1095/ | [
"Gustavo Aguilar",
"Viktor Rozgic",
"Weiran Wang",
"Chao Wang"
] | Studies on emotion recognition (ER) show that combining lexical and acoustic information results in more robust and accurate models. The majority of the studies focus on settings where both modalities are available in training and evaluation. However, in practice, this is not always the case; getting ASR output may rep... | P19-1095 | 10.18653/v1/P19-1095 | null | 1906.10198 | title_snapshot |
P19-1096 | Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts | https://aclanthology.org/P19-1096/ | [
"Rui Xia",
"Zixiang Ding"
] | Emotion cause extraction (ECE), the task aimed at extracting the potential causes behind certain emotions in text, has gained much attention in recent years due to its wide applications. However, it suffers from two shortcomings: 1) the emotion must be annotated before cause extraction in ECE, which greatly limits its ... | P19-1096 | 10.18653/v1/P19-1096 | Outstanding Paper | 1906.01267 | title_snapshot |
P19-1097 | Argument Invention from First Principles | https://aclanthology.org/P19-1097/ | [
"Yonatan Bilu",
"Ariel Gera",
"Daniel Hershcovich",
"Benjamin Sznajder",
"Dan Lahav",
"Guy Moshkowich",
"Anael Malet",
"Assaf Gavron",
"Noam Slonim"
] | Competitive debaters often find themselves facing a challenging task – how to debate a topic they know very little about, with only minutes to prepare, and without access to books or the Internet? What they often do is rely on ”first principles”, commonplace arguments which are relevant to many topics, and which they h... | P19-1097 | 10.18653/v1/P19-1097 | null | 1908.08336 | title_snapshot |
P19-1098 | Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization | https://aclanthology.org/P19-1098/ | [
"Sangwoo Cho",
"Logan Lebanoff",
"Hassan Foroosh",
"Fei Liu"
] | The most important obstacles facing multi-document summarization include excessive redundancy in source descriptions and the looming shortage of training data. These obstacles prevent encoder-decoder models from being used directly, but optimization-based methods such as determinantal point processes (DPPs) are known t... | P19-1098 | 10.18653/v1/P19-1098 | null | 1906.00072 | title_snapshot |
P19-1099 | Global Optimization under Length Constraint for Neural Text Summarization | https://aclanthology.org/P19-1099/ | [
"Takuya Makino",
"Tomoya Iwakura",
"Hiroya Takamura",
"Manabu Okumura"
] | We propose a global optimization method under length constraint (GOLC) for neural text summarization models. GOLC increases the probabilities of generating summaries that have high evaluation scores, ROUGE in this paper, within a desired length. We compared GOLC with two optimization methods, a maximum log-likelihood a... | P19-1099 | 10.18653/v1/P19-1099 | null | null | null |
P19-1100 | Searching for Effective Neural Extractive Summarization: What Works and What’s Next | https://aclanthology.org/P19-1100/ | [
"Ming Zhong",
"Pengfei Liu",
"Danqing Wang",
"Xipeng Qiu",
"Xuanjing Huang"
] | The recent years have seen remarkable success in the use of deep neural networks on text summarization. However, there is no clear understanding of why they perform so well, or how they might be improved. In this paper, we seek to better understand how neural extractive summarization systems could benefit from differen... | P19-1100 | 10.18653/v1/P19-1100 | null | 1907.03491 | title_snapshot |
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