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To date, few attempts have been made to develop and validate methods for au- tomatic evaluation of linguistic quality in text summarization. We present the first systematic assessment of several …...

AbstractThe phenomenon of coreference, covering entities, their mentions and their properties, is intricately linked to the phenomenon of coherence, covering the structure of rhetorical relations in a discourse. A text …...

Recently, researchers have begun explor- ing methods of scoring student essays with respect to particular dimensions of qual- ity such as coherence, technical errors, and relevance to prompt, but there …...

Coherence is what makes a multi-sentence text meaningful, both logically and syn- tactically. To solve the challenge of or- dering a set of sentences into coherent or- der, existing approaches …...

Sarcasm is a form of communication that is intended to mock or harass someone by us- ing words with the opposite of their literal meaning. However, identification of sarcasm is …...

AbstractRecent research on entity linking (EL) has introduced a plethora of promising techniques, ranging from deep neural networks to joint inference. But despite numerous papers there is surprisingly little understanding …...

This paper studies how to incorporate the ex- ternal word correlation knowledge to improve the coherence of topic modeling. Existing topic models assume words are generated in- dependently and lack …...

We present an approach for extractive single-document summarization. Our ap- proach is based on a weighted graphical representation of documents obtained by topic modeling. We optimize importance, coherence and non-redundancy …...

AbstractRule-based stemmers such as the Porter stemmer are frequently used to preprocess English corpora for topic modeling. In this work, we train and evaluate topic models on a variety of …...

AbstractAspect extraction is an important and challenging task in aspect-based sentiment analysis. Existing works tend to apply variants of topic models on this task. While fairly successful, these methods usually …...

AbstractAs a precious part of the human cultural heritage, Chinese poetry has influenced people for generations. Automatic poetry composition is a challenge for AI. In recent years, significant progress has …...

AbstractCross-sentence context can provide valuable information in Machine Translation and is critical for translation of anaphoric pronouns and for providing consistent translations. In this paper, we devise simple oracle experiments …...

AbstractEnterprise content writers are engaged in writing textual content for various purposes. Often, the text being written may already be present in the enterprise corpus in the form of past …...

AbstractWe present a new summary evaluation approach that does not require human model summaries. Our approach exploits the compositional capabilities of corpus-based and lexical resource-based word embeddings to develop the …...

AbstractWhile NLP systems become more pervasive, their accountability gains value as a focal point of effort. Epistemological opaqueness of nonlinear learning methods, such as deep learning models, can be a …...

AbstractTopic 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 …...

AbstractUnderstanding contrastive opinions is a key component of argument generation. Central to an argument is the claim, a statement that is in dispute. Generating a counter-argument then requires generating a …...

AbstractIn this paper, a novel Generation-Evaluation framework is developed for multi-turn conversations with the objective of letting both participants know more about each other. For the sake of rational knowledge …...

AbstractMulti-turn conversations consist of complex semantic structures, and it is still a challenge to generate coherent and diverse responses given previous utterances. It’s practical that a conversation takes place under …...

AbstractEmotion-controllable response generation is an attractive and valuable task that aims to make open-domain conversations more empathetic and engaging. Existing methods mainly enhance the emotion expression by adding regularization terms …...

AbstractDocument-level machine translation focuses on the translation of entire documents from a source to a target language. It is widely regarded as a challenging task since the translation of the …...

AbstractExisting pre-trained large language models have shown unparalleled generative capabilities. However, they are not controllable. In this paper, we propose MEGATRON-CNTRL, a novel framework that uses large-scale language models and …...

AbstractAutomatically generated stories need to be not only coherent, but also interesting. Apart from realizing a story line, the text also needs to include rich details to engage the readers. …...

AbstractSentence ordering is the task of arranging the sentences of a given text in the correct order. Recent work using deep neural networks for this task has framed it as …...

AbstractMany data sets (e.g., reviews, forums, news, etc.) exist parallelly in multiple languages. They all cover the same content, but the linguistic differences make it impossible to use traditional, bag-of-word-based …...

Studies based on linguistic theories have reported that internet celebrities em- ploy various persuasion strategies in their speeches. Since persuasion is closely re- lated to pragmatics which involves peo- ple’s …...

AbstractGenerating some appealing questions in open-domain conversations is an effective way to improve human-machine interactions and lead the topic to a broader or deeper direction. To avoid dull or deviated …...

AbstractManual evaluation is essential to judge progress on automatic text summarization. However, we conduct a survey on recent summarization system papers that reveals little agreement on how to perform such …...

Writing a coherent and engaging story is not easy. Creative writers use their knowledge and worldview to put disjointed elements together to form a coherent storyline, and work and rework …...

AbstractDialogue summarization is receiving increasing attention from researchers due to its extraordinary difficulty and unique application value. We observe that current dialogue summarization models have flaws that may not be …...

AbstractOpen-ended text generation tasks, such as dialogue generation and story completion, require models to generate a coherent continuation given limited preceding context. The open-ended nature of these tasks brings new …...

AbstractDesigning in-depth educational questions is a time-consuming and cognitively demanding task. Therefore, it is intriguing to study how to build Question Generation (QG) models to automate the question creation process. …...

AbstractTeaching neural models to generate narrative coherent texts is a critical problem. Recent pre-trained language models have achieved promising results, but there is still a gap between human written texts …...

AbstractLanguage models have demonstrated the ability to generate highly fluent text; however, it remains unclear whether their output retains coherent high-level structure (e.g., story progression). Here, we propose to apply …...

AbstractWe present a memory-augmented approach to condition an autoregressive language model on a knowledge graph. We represent the graph as a collection of relation triples and retrieve relevant relations for …...

AbstractLong-form question answering (LFQA) enables answering a wide range of questions, but its flexibility poses enormous challenges for evaluation. We perform the first targeted study of the evaluation of long-form …...

AbstractReflection is a crucial counselling skill where the therapist conveys to the client their interpretation of what the client said. Language models have recently been used to generate reflections automatically, …...