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Found 56 papers, 15 papers with code
How to Make Neural Natural Language Generation as Reliable as Templates in Task-Oriented Dialogue
Neural Natural Language Generation (NLG) systems are well known for their unreliability.
A BERT’s Eye View: Identification of Irish Multiword Expressions Using Pre-trained Language Models
This paper reports on the investigation of using pre-trained language models for the identification of Irish verbal multiword expressions (vMWEs), comparing the results with the systems submitted for the PARSEME shared task edition 1. 2.
Annotating Verbal MWEs in Irish for the PARSEME Shared Task 1.2
This paper describes the creation of two Irish corpora (labelled and unlabelled) for verbal MWEs for inclusion in the PARSEME Shared Task 1. 2 on automatic identification of verbal MWEs, and the process of developing verbal MWE categories for Irish.
Naive Bayes versus BERT: Jupyter notebook assignments for an introductory NLP course
We describe two Jupyter notebooks that form the basis of two assignments in an introductory Natural Language Processing (NLP) module taught to final year undergraduate students at Dublin City University.
gaBERT — an Irish Language Model
We compare our gaBERT model to multilingual BERT and the monolingual Irish WikiBERT, and we show that gaBERT provides better representations for a downstream parsing task.
TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish
Modern Irish is a minority language lacking sufficient computational resources for the task of accurate automatic syntactic parsing of user-generated content such as tweets.
Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It’s complicated!
In this paper we explore the problem of machine reading comprehension, focusing on the BoolQ dataset of Yes/No questions.
Tell Me Why: Explainable Public Health Fact-Checking with Large Language Models
This paper presents a comprehensive analysis of explainable fact-checking through a series of experiments, focusing on the ability of large language models to verify public health claims and provide explanations or justifications for their veracity assessments.
Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition
Recent developments in generative AI have shone a spotlight on high-performance synthetic text generation technologies.
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future
Machine learning (ML) systems in natural language processing (NLP) face significant challenges in generalizing to out-of-distribution (OOD) data, where the test distribution differs from the training data distribution.
Is a Video worth $n\times n$ Images? A Highly Efficient Approach to Transformer-based Video Question Answering
We show that by integrating our approach into VideoQA systems we can achieve comparable, even superior, performance with a significant speed up for training and inference.
Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering
Specifically, we explicitly use the Semantic Role Labeling (SRL) structure of the question in the dynamic reasoning process where we decide to move to the next frame based on which part of the SRL structure (agent, verb, patient, etc.)
Dialogue-to-Video Retrieval
Recent years have witnessed an increasing amount of dialogue/conversation on the web especially on social media.
Exploiting Rich Textual User-Product Context for Improving Sentiment Analysis
User and product information associated with a review is useful for sentiment polarity prediction.
Extending the Scope of Out-of-Domain: Examining QA models in multiple subdomains
Past works that investigate out-of-domain performance of QA systems have mainly focused on general domains (e. g. news domain, wikipedia domain), underestimating the importance of subdomains defined by the internal characteristics of QA datasets.
Revisiting Tri-training of Dependency Parsers
We compare two orthogonal semi-supervised learning techniques, namely tri-training and pretrained word embeddings, in the task of dependency parsing.
Improving Unsupervised Question Answering via Summarization-Informed Question Generation
Template-based QG uses linguistically-informed heuristics to transform declarative sentences into interrogatives, whereas supervised QG uses existing Question Answering (QA) datasets to train a system to generate a question given a passage and an answer.
gaBERT -- an Irish Language Model
We compare our gaBERT model to multilingual BERT and the monolingual Irish WikiBERT, and we show that gaBERT provides better representations for a downstream parsing task.
The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task
The task involves parsing Enhanced UD graphs, which are an extension of the basic dependency trees designed to be more facilitative towards representing semantic structure.
English Machine Reading Comprehension Datasets: A Survey
This paper surveys 60 English Machine Reading Comprehension datasets, with a view to providing a convenient resource for other researchers interested in this problem.
Improving Document-Level Sentiment Analysis with User and Product Context
We achieve this by explicitly storing representations of reviews written by the same user and about the same product and force the model to memorize all reviews for one particular user and product.
Fact or Factitious? Contextualized Opinion Spam Detection
In this paper we perform an analytic comparison of a number of techniques used to detect fake and deceptive online reviews.
The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task
Unfortunately, we did not ensure a connected graph as part of our pipeline approach and our competition submission relied on a last-minute fix to pass the validation script which harmed our official evaluation scores significantly.
Shape of synth to come: Why we should use synthetic data for English surface realization
The Surface Realization Shared Tasks of 2018 and 2019 were Natural Language Generation shared tasks with the goal of exploring approaches to surface realization from Universal-Dependency-like trees to surface strings for several languages.
Treebank Embedding Vectors for Out-of-domain Dependency Parsing
A recent advance in monolingual dependency parsing is the idea of a treebank embedding vector, which allows all treebanks for a particular language to be used as training data while at the same time allowing the model to prefer training data from one treebank over others and to select the preferred treebank at test time.
Cross-lingual Parsing with Polyglot Training and Multi-treebank Learning: A Faroese Case Study
Finally, we apply multi-treebank modelling to the projected treebanks, in addition to or alternatively to polyglot modelling on the source side.
Ilfhocail: A Lexicon of Irish MWEs
This paper describes the categorisation of Irish MWEs, and the construction of the first version of a lexicon of Irish MWEs for NLP purposes (Ilfhocail, meaning {`}Multiwords{'}), collected from a number of resources.
Is It Dish Washer Safe? Automatically Answering ``Yes/No'' Questions Using Customer Reviews
It has become commonplace for people to share their opinions about all kinds of products by posting reviews online.
Designing a Symbolic Intermediate Representation for Neural Surface Realization
Generated output from neural NLG systems often contain errors such as hallucination, repetition or contradiction.
Sentiment Expression Boundaries in Sentiment Polarity Classification
We investigate the effect of using sentiment expression boundaries in predicting sentiment polarity in aspect-level sentiment analysis.
Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study
While the original any-gram kernels are implemented on top of tree kernels, we propose a new approach which is independent of tree kernels and is more efficient.
If You Can't Beat Them Join Them: Handcrafted Features Complement Neural Nets for Non-Factoid Answer Reranking
We show that a neural approach to the task of non-factoid answer reranking can benefit from the inclusion of tried-and-tested handcrafted features.
Detecting Opinion Polarities using Kernel Methods
We investigate the application of kernel methods to representing both structural and lexical knowledge for predicting polarity of opinions in consumer product review.
Irish Treebanking and Parsing: A Preliminary Evaluation
This paper describes the early stages in the development of new language resources for Irish ― namely the first Irish dependency treebank and the first Irish statistical dependency parser.
