Articles

AbstractVisual Question Answering (VQA) remains algorithmically challenging while it is effortless for humans. Humans combine visual observations with general and commonsense knowledge to answer questions about a given image. In this paper, we address the problem of incorporating general knowledge into VQA models while leveraging the visual information. We propose …...

AbstractMultimodal named entity recognition (MNER) for tweets has received increasing attention recently. Most of the multimodal methods used attention mechanisms to capture the text-related visual information. However, unrelated or weakly related text-image pairs account for a large proportion in tweets. Visual clues unrelated to the text would incur uncertain or …...

AbstractTemporal sentence localization in videos aims to ground the best matched segment in an untrimmed video according to a given sentence query. Previous works in this field mainly rely on attentional frameworks to align the temporal boundaries by a soft selection. Although they focus on the visual content relevant to …...

AbstractThe automatic feedback of school assignments is an important application of AI in education. In this work, we focus on the task of personalized multimodal feedback generation, which aims to generate personalized feedback for teachers to evaluate students’ assignments involving multimodal inputs such as images, audios, and texts. This task …...

AbstractModern task-oriented dialog systems need to reliably understand users’ intents. Intent detection is even more challenging when moving to new domains or new languages, since there is little annotated data. To address this challenge, we present a suite of pretrained intent detection models which can predict a broad range of …...

AbstractWe release ManyNames v2 (MN v2), a verified version of an object naming dataset that contains dozens of valid names per object for 25K images. We analyze issues in the data collection method originally employed, standard in Language & Vision (L&V), and find that the main source of noise in …...

AbstractCommitments and requests are a hallmark of collaborative communication, especially in team settings. Identifying specific tasks being committed to or request from emails and chat messages can enable important downstream tasks, such as producing todo lists, reminders, and calendar entries. State-of-the-art approaches for task identification rely on large annotated datasets, …...

AbstractControllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated natural language caption. This puts a stronger focus on producing more detailed descriptions, and opens the door for more end-user …...

AbstractCode-switching has long interested linguists, with computational work in particular focusing on speech and social media data (Sitaram et al., 2019). This paper contrasts these informal instances of code-switching to its appearance in more formal registers, by examining the mixture of languages in the Deutsches Textarchiv (DTA), a corpus of …...

AbstractPredicting users’ opinions in their response to social events has important real-world applications, many of which political and social impacts. Existing approaches derive a population’s opinion on a going event from large scores of user generated content. In certain scenarios, we may not be able to acquire such content and …...

AbstractOne of the cardinal tasks in achieving robust medical question answering systems is textual entailment. The existing approaches make use of an ensemble of pre-trained language models or data augmentation, often to clock higher numbers on the validation metrics. However, two major shortcomings impede higher success in identifying entailment: (1) …...

AbstractEvents in a narrative differ in salience: some are more important to the story than others. Estimating event salience is useful for tasks such as story generation, and as a tool for text analysis in narratology and folkloristics. To compute event salience without any annotations, we adopt Barthes’ definition of …...

AbstractNative language identification (NLI) – identifying the native language (L1) of a person based on his/her writing in the second language (L2) – is useful for a variety of purposes, including marketing, security, and educational applications. From a traditional machine learning perspective,NLI is usually framed as a multi-class classification task, …...

AbstractFact verification models have enjoyed a fast advancement in the last two years with the development of pre-trained language models like BERT and the release of large scale datasets such as FEVER. However, the challenging problem of fake news detection has not benefited from the improvement of fact verification models, …...

AbstractA fundamental task of fine-grained sentiment analysis is aspect and opinion terms extraction. Supervised-learning approaches have shown good results for this task; however, they fail to scale across domains where labeled data is lacking. Non pre-trained unsupervised domain adaptation methods that incorporate external linguistic knowledge have proven effective in transferring …...

AbstractAbstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence. This paper provides a novel approach to this task. We first introduce a neural contextual utterance encoder featuring …...

AbstractIn formal semantics, there are two well-developed semantic frameworks: event semantics, which treats verbs and adverbial modifiers using the notion of event, and degree semantics, which analyzes adjectives and comparatives using the notion of degree. However, it is not obvious whether these frameworks can be combined to handle cases in …...

AbstractWord sense disambiguation (WSD) is a fundamental natural language processing task. Unsupervised knowledge-based WSD only relies on a lexical knowledge base as the sense inventory and has wider practical use than supervised WSD that requires a mass of sense-annotated data. HowNet is the most widely used lexical knowledge base in …...

AbstractMuch previous work on geoparsing has focused on identifying and resolving individual toponyms in text like Adrano, S.Maria di Licodia or Catania. However, geographical locations occur not only as individual toponyms, but also as compositions of reference geolocations joined and modified by connectives, e.g., “. . . between the towns …...

AbstractThis paper brings together approaches from the fields of NLP and psychometric measurement to address the problem of predicting examinee proficiency from responses to short-answer questions (SAQs). While previous approaches train on manually labeled data to predict the human-ratings assigned to SAQ responses, the approach presented here models examinee proficiency …...