Paper Group NANR 7
Generating Contrastive Referring Expressions. Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes. Correlation Analysis of Chronic Obstructive Pulmonary Disease (COPD) and its Biomarkers Using the Word Embeddings. A Practical Perspective on Latent Structured Prediction for Coreference Resolution. Identifying Effective Tran …
Generating Contrastive Referring Expressions
| Title | Generating Contrastive Referring Expressions |
| Authors | Mart{'\i}n Villalba, Christoph Teichmann, Alex Koller, er |
| Abstract | The referring expressions (REs) produced by a natural language generation (NLG) system can be misunderstood by the hearer, even when they are semantically correct. In an interactive setting, the NLG system can try to recognize such misunderstandings and correct them. We present an algorithm for generating corrective REs that use contrastive focus ({``}no, the BLUE button{''}) to emphasize the information the hearer most likely misunderstood. We show empirically that these contrastive REs are preferred over REs without contrast marking. | |
| Tasks | Text Generation |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-1063/ |
| https://www.aclweb.org/anthology/P17-1063 | |
| PWC | https://paperswithcode.com/paper/generating-contrastive-referring-expressions |
| Repo | |
| Framework | |
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
| Title | Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes |
| Authors | Jianshu Chen, Chong Wang, Lin Xiao, Ji He, Lihong Li, Li Deng |
| Abstract | In sequential decision making, it is often important and useful for end users to understand the underlying patterns or causes that lead to the corresponding decisions. However, typical deep reinforcement learning algorithms seldom provide such information due to their black-box nature. In this paper, we present a probabilistic model, Q-LDA, to uncover latent patterns in text-based sequential decision processes. The model can be understood as a variant of latent topic models that are tailored to maximize total rewards; we further draw an interesting connection between an approximate maximum-likelihood estimation of Q-LDA and the celebrated Q-learning algorithm. We demonstrate in the text-game domain that our proposed method not only provides a viable mechanism to uncover latent patterns in decision processes, but also obtains state-of-the-art rewards in these games. |
| Tasks | Decision Making, Q-Learning, Topic Models |
| Published | 2017-12-01 |
| URL | http://papers.nips.cc/paper/7083-q-lda-uncovering-latent-patterns-in-text-based-sequential-decision-processes |
| http://papers.nips.cc/paper/7083-q-lda-uncovering-latent-patterns-in-text-based-sequential-decision-processes.pdf | |
| PWC | https://paperswithcode.com/paper/q-lda-uncovering-latent-patterns-in-text |
| Repo | |
| Framework | |
Correlation Analysis of Chronic Obstructive Pulmonary Disease (COPD) and its Biomarkers Using the Word Embeddings
| Title | Correlation Analysis of Chronic Obstructive Pulmonary Disease (COPD) and its Biomarkers Using the Word Embeddings |
| Authors | Byeong-Hun Yoon, Yu-Seop Kim |
| Abstract | It is very costly and time consuming to find new biomarkers for specific diseases in clinical laboratories. In this study, to find new biomarkers most closely related to Chronic Obstructive Pulmonary Disease (COPD), which is widely known as respiratory disease, biomarkers known to be associated with respiratory diseases and COPD itself were converted into word embedding. And their similarities were measured. We used Word2Vec, Canonical Correlation Analysis (CCA), and Global Vector (GloVe) for word embedding. In order to replace the clinical evaluation, the titles and abstracts of papers retrieved from Google Scholars were analyzed and quantified to estimate the performance of the word em-bedding models. |
| Tasks | Word Embeddings |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/I17-2057/ |
| https://www.aclweb.org/anthology/I17-2057 | |
| PWC | https://paperswithcode.com/paper/correlation-analysis-of-chronic-obstructive |
| Repo | |
| Framework | |
A Practical Perspective on Latent Structured Prediction for Coreference Resolution
| Title | A Practical Perspective on Latent Structured Prediction for Coreference Resolution |
| Authors | Iryna Haponchyk, Aless Moschitti, ro |
| Abstract | Latent structured prediction theory proposes powerful methods such as Latent Structural SVM (LSSVM), which can potentially be very appealing for coreference resolution (CR). In contrast, only small work is available, mainly targeting the latent structured perceptron (LSP). In this paper, we carried out a practical study comparing for the first time online learning with LSSVM. We analyze the intricacies that may have made initial attempts to use LSSVM fail, i.e., a huge training time and much lower accuracy produced by Kruskal{'}s spanning tree algorithm. In this respect, we also propose a new effective feature selection approach for improving system efficiency. The results show that LSP, if correctly parameterized, produces the same performance as LSSVM, being much more efficient. |
| Tasks | Coreference Resolution, Feature Selection, Structured Prediction, Text Categorization |
| Published | 2017-04-01 |
| URL | https://www.aclweb.org/anthology/E17-2023/ |
| https://www.aclweb.org/anthology/E17-2023 | |
| PWC | https://paperswithcode.com/paper/a-practical-perspective-on-latent-structured |
| Repo | |
| Framework | |
Identifying Effective Translations for Cross-lingual Arabic-to-English User-generated Speech Search
| Title | Identifying Effective Translations for Cross-lingual Arabic-to-English User-generated Speech Search |
| Authors | Ahmad Khwileh, Haithem Afli, Gareth Jones, Andy Way |
| Abstract | Cross Language Information Retrieval (CLIR) systems are a valuable tool to enable speakers of one language to search for content of interest expressed in a different language. A group for whom this is of particular interest is bilingual Arabic speakers who wish to search for English language content using information needs expressed in Arabic queries. A key challenge in CLIR is crossing the language barrier between the query and the documents. The most common approach to bridging this gap is automated query translation, which can be unreliable for vague or short queries. In this work, we examine the potential for improving CLIR effectiveness by predicting the translation effectiveness using Query Performance Prediction (QPP) techniques. We propose a novel QPP method to estimate the quality of translation for an Arabic-English Cross-lingual User-generated Speech Search (CLUGS) task. We present an empirical evaluation that demonstrates the quality of our method on alternative translation outputs extracted from an Arabic-to-English Machine Translation system developed for this task. Finally, we show how this framework can be integrated in CLUGS to find relevant translations for improved retrieval performance. |
| Tasks | Information Retrieval, Machine Translation |
| Published | 2017-04-01 |
| URL | https://www.aclweb.org/anthology/W17-1313/ |
| https://www.aclweb.org/anthology/W17-1313 | |
| PWC | https://paperswithcode.com/paper/identifying-effective-translations-for-cross |
| Repo | |
| Framework | |
A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring
| Title | A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring |
| Authors | Nitin Madnani, Anastassia Loukina, Aoife Cahill |
| Abstract | We explore various supervised learning strategies for automated scoring of content knowledge for a large corpus of 130 different content-based questions spanning four subject areas (Science, Math, English Language Arts, and Social Studies) and containing over 230,000 responses scored by human raters. Based on our analyses, we provide specific recommendations for content scoring. These are based on patterns observed across multiple questions and assessments and are, therefore, likely to generalize to other scenarios and prove useful to the community as automated content scoring becomes more popular in schools and classrooms. |
| Tasks | |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-5052/ |
| https://www.aclweb.org/anthology/W17-5052 | |
| PWC | https://paperswithcode.com/paper/a-large-scale-quantitative-exploration-of |
| Repo | |
| Framework | |
Discriminative State Space Models
| Title | Discriminative State Space Models |
| Authors | Vitaly Kuznetsov, Mehryar Mohri |
| Abstract | In this paper, we introduce and analyze Discriminative State-Space Models for forecasting non-stationary time series. We provide data-dependent generalization guarantees for learning these models based on the recently introduced notion of discrepancy. We provide an in-depth analysis of the complexity of such models. Finally, we also study the generalization guarantees for several structural risk minimization approaches to this problem and provide an efficient implementation for one of them which is based on a convex objective. |
| Tasks | Time Series |
| Published | 2017-12-01 |
| URL | http://papers.nips.cc/paper/7150-discriminative-state-space-models |
| http://papers.nips.cc/paper/7150-discriminative-state-space-models.pdf | |
| PWC | https://paperswithcode.com/paper/discriminative-state-space-models |
| Repo | |
| Framework | |
Revisiting the Variable Projection Method for Separable Nonlinear Least Squares Problems
| Title | Revisiting the Variable Projection Method for Separable Nonlinear Least Squares Problems |
| Authors | Je Hyeong Hong, Christopher Zach, Andrew Fitzgibbon |
| Abstract | Variable Projection (VarPro) is a framework to solve optimization problems efficiently by optimally eliminating a subset of the unknowns. It is in particular adapted for Separable Nonlinear Least Squares (SNLS) problems, a class of optimization problems including low-rank matrix factorization with missing data and affine bundle adjustment as instances. VarPro-based methods have received much attention over the last decade due to the experimentally observed large convergence basin for certain problem classes, where they have a clear advantage over standard methods based on Joint optimization over all unknowns. Yet no clear answers have been found in the literature as to why VarPro outperforms others and why Joint optimization, which has been successful in solving many computer vision tasks, fails on this type of problems. Also, the fact that VarPro has been mainly tested on small to medium-sized datasets has raised questions about its scalability. This paper intends to address these unsolved puzzles. |
| Tasks | |
| Published | 2017-07-01 |
| URL | http://openaccess.thecvf.com/content_cvpr_2017/html/Hong_Revisiting_the_Variable_CVPR_2017_paper.html |
| http://openaccess.thecvf.com/content_cvpr_2017/papers/Hong_Revisiting_the_Variable_CVPR_2017_paper.pdf | |
| PWC | https://paperswithcode.com/paper/revisiting-the-variable-projection-method-for |
| Repo | |
| Framework | |
Deception Detection in News Reports in the Russian Language: Lexics and Discourse
| Title | Deception Detection in News Reports in the Russian Language: Lexics and Discourse |
| Authors | Dina Pisarevskaya |
| Abstract | News verification and automated fact checking tend to be very important issues in our world. The research is initial. We collected a corpus for Russian (174 news reports, truthful and fake ones). We held two experiments, for both we applied SVMs algorithm (linear/rbf kernel) and Random Forest to classify the news reports into 2 classes: truthful/deceptive. In the first experiment, we used 18 markers on lexics level, mostly frequencies of POS tags in texts. In the second experiment, on discourse level we used frequencies of rhetorical relations types in texts. The classification task in the first experiment is solved better by SVMs (rbf kernel) (f-measure 0.65). The model based on RST features shows best results with Random Forest Classifier (f-measure 0.54) and should be modified. In the next research, the combination of different deception detection markers for the Russian language should be taken in order to make a better predictive model. |
| Tasks | Deception Detection, Fake News Detection, Question Answering, Rumour Detection, Text Classification |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-4213/ |
| https://www.aclweb.org/anthology/W17-4213 | |
| PWC | https://paperswithcode.com/paper/deception-detection-in-news-reports-in-the |
| Repo | |
| Framework | |
Experimental Design for Learning Causal Graphs with Latent Variables
| Title | Experimental Design for Learning Causal Graphs with Latent Variables |
| Authors | Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim |
| Abstract | We consider the problem of learning causal structures with latent variables using interventions. Our objective is not only to learn the causal graph between the observed variables, but to locate unobserved variables that could confound the relationship between observables. Our approach is stage-wise: We first learn the observable graph, i.e., the induced graph between observable variables. Next we learn the existence and location of the latent variables given the observable graph. We propose an efficient randomized algorithm that can learn the observable graph using O(d\log^2 n) interventions where d is the degree of the graph. We further propose an efficient deterministic variant which uses O(log n + l) interventions, where l is the longest directed path in the graph. Next, we propose an algorithm that uses only O(d^2 log n) interventions that can learn the latents between both non-adjacent and adjacent variables. While a naive baseline approach would require O(n^2) interventions, our combined algorithm can learn the causal graph with latents using O(d log^2 n + d^2 log (n)) interventions. |
| Tasks | |
| Published | 2017-12-01 |
| URL | http://papers.nips.cc/paper/7277-experimental-design-for-learning-causal-graphs-with-latent-variables |
| http://papers.nips.cc/paper/7277-experimental-design-for-learning-causal-graphs-with-latent-variables.pdf | |
| PWC | https://paperswithcode.com/paper/experimental-design-for-learning-causal |
| Repo | |
| Framework | |
From Shakespeare to Twitter: What are Language Styles all about?
| Title | From Shakespeare to Twitter: What are Language Styles all about? |
| Authors | Wei Xu |
| Abstract | As natural language processing research is growing and largely driven by the availability of data, we expanded research from news and small-scale dialog corpora to web and social media. User-generated data and crowdsourcing opened the door for investigating human language of various styles with more statistical power and real-world applications. In this position/survey paper, I will review and discuss seven language styles that I believe to be important and interesting to study: influential work in the past, challenges at the present, and potential impact for the future. |
| Tasks | Lexical Simplification, Question Answering, Text Simplification |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-4901/ |
| https://www.aclweb.org/anthology/W17-4901 | |
| PWC | https://paperswithcode.com/paper/from-shakespeare-to-twitter-what-are-language |
| Repo | |
| Framework | |
Combating Human Trafficking with Multimodal Deep Models
| Title | Combating Human Trafficking with Multimodal Deep Models |
| Authors | Edmund Tong, Amir Zadeh, Cara Jones, Louis-Philippe Morency |
| Abstract | Human trafficking is a global epidemic affecting millions of people across the planet. Sex trafficking, the dominant form of human trafficking, has seen a significant rise mostly due to the abundance of escort websites, where human traffickers can openly advertise among at-will escort advertisements. In this paper, we take a major step in the automatic detection of advertisements suspected to pertain to human trafficking. We present a novel dataset called Trafficking-10k, with more than 10,000 advertisements annotated for this task. The dataset contains two sources of information per advertisement: text and images. For the accurate detection of trafficking advertisements, we designed and trained a deep multimodal model called the Human Trafficking Deep Network (HTDN). |
| Tasks | |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-1142/ |
| https://www.aclweb.org/anthology/P17-1142 | |
| PWC | https://paperswithcode.com/paper/combating-human-trafficking-with-multimodal |
| Repo | |
| Framework | |
Information Navigation System with Discovering User Interests
| Title | Information Navigation System with Discovering User Interests |
| Authors | Koichiro Yoshino, Yu Suzuki, Satoshi Nakamura |
| Abstract | We demonstrate an information navigation system for sightseeing domains that has a dialogue interface for discovering user interests for tourist activities. The system discovers interests of a user with focus detection on user utterances, and proactively presents related information to the discovered user interest. A partially observable Markov decision process (POMDP)-based dialogue manager, which is extended with user focus states, controls the behavior of the system to provide information with several dialogue acts for providing information. We transferred the belief-update function and the policy of the manager from other system trained on a different domain to show the generality of defined dialogue acts for our information navigation system. |
| Tasks | Semantic Textual Similarity, Speech Recognition |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-5542/ |
| https://www.aclweb.org/anthology/W17-5542 | |
| PWC | https://paperswithcode.com/paper/information-navigation-system-with |
| Repo | |
| Framework | |
The Circumstantial Event Ontology (CEO)
| Title | The Circumstantial Event Ontology (CEO) |
| Authors | Roxane Segers, Tommaso Caselli, Piek Vossen |
| Abstract | In this paper we describe the ongoing work on the Circumstantial Event Ontology (CEO), a newly developed ontology for calamity events that models semantic circumstantial relations between event classes. The circumstantial relations are designed manually, based on the shared properties of each event class. We discuss and contrast two types of event circumstantial relations: semantic circumstantial relations and episodic circumstantial relations. Further, we show the metamodel and the current contents of the ontology and outline the evaluation of the CEO. |
| Tasks | |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2706/ |
| https://www.aclweb.org/anthology/W17-2706 | |
| PWC | https://paperswithcode.com/paper/the-circumstantial-event-ontology-ceo |
| Repo | |
| Framework | |
On the Predicate-Argument Structure: Internal and Absorbing Scope
| Title | On the Predicate-Argument Structure: Internal and Absorbing Scope |
| Authors | Igor Boguslavsky |
| Abstract | |
| Tasks | Slot Filling |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-6504/ |
| https://www.aclweb.org/anthology/W17-6504 | |
| PWC | https://paperswithcode.com/paper/on-the-predicate-argument-structure-internal |
| Repo | |
| Framework | |
