Человеческие суждения

Title generation is a complex task involving both natural language understanding and natural language synthesis. In this paper, we propose a new probabilistic model for title generation. Different from the …...

Previous work on the induction of se- lectional preferences has been mainly carried out for English and has concen- trated almost exclusively on verbs and their direct objects. In this …...

We present a novel approach for discov- ering word categories, sets of words shar- ing a significant aspect of their mean- ing. We utilize meta-patterns of high- frequency words and …...

Semantic relatedness between words is important to many NLP tasks, and nu- merous measures exist which use a vari- ety of resources. Thus far, such work is confined to measuring …...

This paper presents a new, exemplar-based model of thematic fit. In contrast to pre- vious models, it does not approximate thematic fit as argument plausibility or ‘fit with verb selectional …...

Sets of lexical items sharing a significant aspect of their meaning (concepts) are fun- damental in linguistics and NLP. Manual concept compilation is labor intensive, er- ror prone and subjective. …...

We present the results of a large-scale, end-to-end human evaluation of various sentiment summarization models. The evaluation shows that users have a strong preference for summarizers that model sentiment over …...

We present a method which, given a few words defining a concept in some lan- guage, retrieves, disambiguates and ex- tends corresponding terms that define a similar concept in another …...

This paper presents the results of the WMT10 and MetricsMATR10 shared tasks,1 which included a translation task, a system combination task, and an eval- uation task. We conducted a large-scale …...

This paper presents an empirical comparison of similarity measures for pairs of concepts based on Information Content. It shows that using modest amounts of untagged text to de- rive Information …...

Social scientists are increasingly using the vast amount of text available on social me- dia to measure variation in happiness and other psychological states. Such studies count words deemed to …...

Using automatic measures such as labeled and unlabeled attachment scores is com- mon practice in dependency parser evalu- ation. In this paper, we examine whether these measures correlate with human …...

Natural language acquisition relies on appro- priate generalization: the ability to produce novel sentences, while learning to restrict pro- ductions to acceptable forms in the language. Psycholinguists have proposed various …...

Idioms pose a great challenge to natural lan- guage understanding. A system that can auto- matically paraphrase idioms in context has ap- plications in many NLP tasks. This paper pro- …...

AbstractThere have been several attempts to define a plausible motivation for a chit-chat dialogue agent that can lead to engaging conversations. In this work, we explore a new direction where …...

AbstractLexical simplification involves identifying complex words or phrases that need to be simplified, and recommending simpler meaning-preserving substitutes that can be more easily understood. We propose a complex word identification …...

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 …...

Stereotypes are inferences drawn about people based on their demographic attributes, which may result in harms to users when a system is deployed. In generative language-inference tasks, given a premise, …...

We introduce a novel dataset of human judg- ments of machine-edited text and initial mod- els of those perceptions. Six machine-editing methods ranging from character swapping to variational autoencoders are …...

AbstractRecent text generation research has increasingly focused on open-ended domains such as story and poetry generation. Because models built for such tasks are difficult to evaluate automatically, most researchers in …...

AbstractThis study carries out a systematic intrinsic evaluation of the semantic representations learned by state-of-the-art pre-trained multimodal Transformers. These representations are claimed to be task-agnostic and shown to help on …...

AbstractKnowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-3 to give acceptability judgments …...