Search Results for author:
Found 29 papers, 4 papers with code
Exploring Italian sentence embeddings properties through multi-tasking
We investigate to what degree existing LLMs encode abstract linguistic information in Italian in a multi-task setting.
Exploring syntactic information in sentence embeddings through multilingual subject-verb agreement
In this paper, our goal is to investigate to what degree multilingual pretrained language models capture cross-linguistically valid abstract linguistic representations.
Tracking linguistic information in transformer-based sentence embeddings through targeted sparsification
Analyses of transformer-based models have shown that they encode a variety of linguistic information from their textual input.
Are there identifiable structural parts in the sentence embedding whole?
Sentence embeddings from transformer models encode in a fixed length vector much linguistic information.
Disentangling continuous and discrete linguistic signals in transformer-based sentence embeddings
We explore whether we can compress transformer-based sentence embeddings into a representation that separates different linguistic signals -- in particular, information relevant to subject-verb agreement and verb alternations.
Grammatical information in BERT sentence embeddings as two-dimensional arrays
Next, we show that various architectures can detect patterns in these two-dimensional reshaped sentence embeddings and successfully learn a model based on smaller amounts of simpler training data, which performs well on more complex test data.
Semantic Relations and Deep Learning
The second edition of "Semantic Relations Between Nominals" by Vivi Nastase, Stan Szpakowicz, Preslav Nakov and Diarmuid \'O S\'eaghdha has been published in April 2021 by Morgan & Claypool (www. morganclaypoolpublishers. com/catalog_Orig/product_info. php? products_id=1627).
Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines
We introduce a new dataset consisting of natural language interactions annotated with medical family histories, obtained during interactions with a genetic counselor and through crowdsourcing, following a questionnaire created by experts in the domain.
Anglicized Words and Misspelled Cognates in Native Language Identification
In this paper, we present experiments that estimate the impact of specific lexical choices of people writing in a second language (L2).
Metaphors in Text Simplification: To change or not to change, that is the question
We present an analysis of metaphors in news text simplification.
Abstract Graphs and Abstract Paths for Knowledge Graph Completion
Knowledge graphs, which provide numerous facts in a machine-friendly format, are incomplete.
Assessing the Difficulty of Classifying ConceptNet Relations in a Multi-Label Classification Setting
Commonsense knowledge relations are crucial for advanced NLU tasks.
The Role of Emotions in Native Language Identification
We explore the hypothesis that emotion is one of the dimensions of language that surfaces from the native language into a second language.
Induction of a Large-Scale Knowledge Graph from the Regesta Imperii
We induce and visualize a Knowledge Graph over the Regesta Imperii (RI), an important large-scale resource for medieval history research.
Punctuation as Native Language Interference
In this paper, we describe experiments designed to explore and evaluate the impact of punctuation marks on the task of native language identification.
Word Etymology as Native Language Interference
We present experiments that show the influence of native language on lexical choice when producing text in another language {--} in this particular case English.
Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs
We note a marked difference in the impact of these sampling methods on the two datasets, with the "traditional" corrupting positives method leading to best results on WN18, while embedding based methods benefiting the task on FB15k.
Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention
Detecting aspectual properties of clauses in the form of situation entity types has been shown to depend on a combination of syntactic-semantic and contextual features.
Improving Native Language Identification by Using Spelling Errors
We note that character n-grams from misspelled words are very indicative of the native language of the author.
Learning Knowledge Graph Embeddings with Type Regularizer
Learning relations based on evidence from knowledge bases relies on processing the available relation instances.
Coarse-grained Cross-lingual Alignment of Comparable Texts with Topic Models and Encyclopedic Knowledge
We present a method for coarse-grained cross-lingual alignment of comparable texts: segments consisting of contiguous paragraphs that discuss the same theme (e. g. history, economy) are aligned based on induced multilingual topics.
Mapping WordNet Domains, WordNet Topics and Wikipedia Categories to Generate Multilingual Domain Specific Resources
In this paper we present the mapping between WordNet domains and WordNet topics, and the emergent Wikipedia categories.
Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles
This paper describes the derivation of distributional semantic representations for open class words relative to a concept inventory, and of concepts relative to open class words through grammatical relations extracted from Wikipedia articles.
