Articles

AbstractVisual Relationship Detection aims to understand real-world objects’ interactions by grounding visual concepts to compositional visual relation triples, written in the form of (subject, predicate, object). Previous works have explored the use of contrastive learning to implicitly predict the predicates from the relevant image regions. However, these models often directly …...

AbstractWe introduce Textstar, a graph-based summarization and keyphrase extraction system that builds a document graph using only lemmatization and POS tagging. The document graph aggregates connections between lemma and sentence identifier nodes. Consecutive lemmas in each sentence, as well as consecutive sentences themselves, are connected in rings to form a …...

s Abdul Aziz, Md. Akram Hossain, and Abu Nowshed Chy Department of Computer Science and Engineering University of Chittagong, Chattogram-4331, Bangladesh {aziz.abdul.cu, akram.hossain.cse.cu}@gmail.com, and nowshed@cu.ac.bd Abstract Evidence-based medicine (EBM) is defined as making clinical decisions about individual pa- tients based on the best available evidence. It is beneficial for making …...

AbstractThis paper describes an investigation of establishing communication between a quadro- tor and a human by means of qualitative spatial relations using speech recognition. It is based on a system capable to receive, interpret, process, act, transmit and execute the commands given. This system is composed of a quadrotor equipped …...

AbstractThe log files generated by networked computer systems contain valuable information that can be used to monitor system security and stability. Recently, techniques based on Deep Learning and Natural Language Processing have been proven effective in detecting anomalous activities from system logs. The current approaches, however, have limited practical application …...

AbstractIn recent years, researchers have developed question-answering based approaches to automatically evaluate system summaries, reporting improved validity compared to word overlap-based metrics like ROUGE, in terms of correlation with human ratings of criteria including fluency and hallucination. In this paper, we take a closer look at one particular metric, QuestEval, …...

AbstractThe 2022 ALTA shared task has been running annually since 2010. This year, the shared task is a re-visit of the 2012 ALTA shared task. The purpose of this task is to classify sentences of medical publications using the PIBOSO taxonomy. This is a multi-label classification task which can help …...

AbstractZhangzhou Southern Min employs the airstream mechanism of glottalic ingressive as a contrastive feature in its onset system. However, their realisations are highly diverse with eleven phonetic variants that can be derived from three implosive phonemes (/ɓ, ɗ, ɠ/). The allophonic variations are regressively motivated by three driving factors comprising …...

Deep neural networks show superior perfor- mance in text classification tasks, but their poor interpretability and explainability can cause trust issues. For text classification problems, the identification of textual sub-phrases or “ra- tionales” is one strategy for attempting to find the most influential portions of text, which can be conveyed …...

In this paper, we address the problem of auto- matic academic curriculum generation. A curricu- lum outlines definitive topics with their sub-topics and enables teachers and students to form an over- all idea of the course outcomes and goals, and a plan of what to teach and learn to achieve …...

This study investigates how the reliability of likelihood ratio (LR)-based forensic text comparison (FTC) systems is affected by the sampling variability regarding author numbers in databases. When 30–40 authors (each contributing two 4 kB documents) are included in each of the test, reference and calibration databases, the experimental results demonstrate: …...

Various methods have been proposed to generate code-switched texts. Many of these involve training neural networks and, in turn, require some (albeit small) amounts of code-switched texts or parallel corpora to train the model itself. In this pa- per, we propose a method to convert mono- lingual text into a …...

The analysis of short text documents has be- come a vital and challenging task. Topic mod- els are utilized to extract topics from a large amount of text data. However, these topic mod- els typically suffer from data sparsity problems when applied to short texts because of relatively lower word …...

Modeling text-based time-series to make pre- diction about a future event or outcome is an important task with a wide range of applica- tions. The standard approach is to train and test the model using the same input window, but this approach neglects the data collected in longer input windows …...

AbstractClimate change is an existential threat to humanity, the proliferation of unsubstantiated claims relating to climate science is manipulating public perception, motivating the need for fact-checking in climate science. In this work, we draw on recent work that uses retrieval-augmented generation for veracity prediction and explanation generation, in framing explanation …...

We argue that declarative programs can be writ- ten in precise natural language and back this claim by using a complex optimisation prob- lem. The problem specification is expressed in natural language and automatically translated into an executable answer set program, and an answer set solver is then used to …...

Recent studies in automatic readability assess- ment have shown that hybrid models — mod- els that leverage both linguistically motivated features and neural models — can outperform neural models. However, most evaluations on hybrid models have been based on in-domain data in English. This paper provides further evidence on the …...

In this paper we investigated two different meth- ods to parse relative and noun complement clauses in English and resorted to distinct tags for their corresponding that as a relative pro- noun and as a complementizer. We used an algorithm to relabel a corpus parsed with the GUM Treebank using …...

APPRAISAL is widely used by linguists to study how people judge things or people. Au- tomating APPRAISAL could be beneficial for use cases such as moderating online com- ments. In 2020, the Australasian Language Technology Association (ALTA) organised a shared task to classify a branch APPRAISAL, which involves how humans …...

Multi-hop reading comprehension requires not only the ability to reason over raw text but also the ability to combine multiple evidence. We propose a novel learning approach that helps language models better understand dif- ficult multi-hop questions and perform “com- plex, compositional” reasoning. Our model first learns to decompose each …...