49 citations · 129 across the 19 of their papers we have counts for
21 papers
Exploring the features used for summary evaluation by Human and GPT
Zahra Sadeghi, Evangelos Milios, Frank Rudzicz
Summary assessment involves evaluating how well a generated summary reflects the key ideas and meaning of the source text, requiring a deep understanding of the content. Large Lang…
Sensitivity of Generative VLMs to Semantically and Lexically Altered Prompts
Sri Harsha Dumpala, Aman Jaiswal, Chandramouli Sastry +3
Despite the significant influx of prompt-tuning techniques for generative vision-language models (VLMs), it remains unclear how sensitive these models are to lexical and semantic a…
SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations
Sri Harsha Dumpala, Aman Jaiswal, Chandramouli Sastry +3
Despite their remarkable successes, state-of-the-art large language models (LLMs), including vision-and-language models (VLMs) and unimodal language models (ULMs), fail to understa…
VISLA Benchmark: Evaluating Embedding Sensitivity to Semantic and Lexical Alterations
Sri Harsha Dumpala, Aman Jaiswal, Chandramouli Sastry +3
Despite their remarkable successes, state-of-the-art language models face challenges in grasping certain important semantic details. This paper introduces the VISLA (Variance and I…
Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning
Maksym Taranukhin, Vered Shwartz, Evangelos Milios
Social media platforms are rich sources of opinionated content. Stance detection allows the automatic extraction of users' opinions on various topics from such content. We focus on…
Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights
Maksym Taranukhin, Sahithya Ravi, Gabor Lukacs +2
The Canadian air travel sector has seen a significant increase in flight delays, cancellations, and other issues concerning passenger rights. Recognizing this demand, we present a…
Breaking the Token Barrier: Chunking and Convolution for Efficient Long Text Classification with BERT
Aman Jaiswal, Evangelos Milios
Transformer-based models, specifically BERT, have propelled research in various NLP tasks. However, these models are limited to a maximum token limit of 512 tokens. Consequently, t…
MPTopic: Improving topic modeling via Masked Permuted pre-training
Xinche Zhang, Evangelos milios
Topic modeling is pivotal in discerning hidden semantic structures within texts, thereby generating meaningful descriptive keywords. While innovative techniques like BERTopic and T…
QuOTeS: Query-Oriented Technical Summarization
Juan Ramirez-Orta, Eduardo Xamena, Ana Maguitman +3
Abstract. When writing an academic paper, researchers often spend considerable time reviewing and summarizing papers to extract relevant citations and data to compose the Introduct…
DimenFix: A novel meta-dimensionality reduction method for feature preservation
Qiaodan Luo, Leonardo Christino, Fernando V Paulovich +1
Dimensionality reduction has become an important research topic as demand for interpreting high-dimensional datasets has been increasing rapidly in recent years. There have been ma…
A Theoretical Approach for Structuring and Analysing Knowledge Provenance for Visual Analytics
Leonardo Christino, Sima Rezaeipourfarsangi, Evangelos Milios +1
The primary goal of Visual Analytics (VA) is to enable user-guided knowledge generation. Theoretical VA works to explain how the different aspects of a VA tool bring forth new insi…
Post-OCR Document Correction with large Ensembles of Character Sequence-to-Sequence Models
Juan Ramirez-Orta, Eduardo Xamena, Ana Maguitman +2
In this paper, we propose a novel method based on character sequence-to-sequence models to correct documents already processed with Optical Character Recognition (OCR) systems. The…
Neural Abstractive Unsupervised Summarization of Online News Discussions
Ignacio Tampe Palma, Marcelo Mendoza, Evangelos Milios
Summarization has usually relied on gold standard summaries to train extractive or abstractive models. Social media brings a hurdle to summarization techniques since it requires ad…
Active learning for medical code assignment
Martha Dais Ferreira, Michal Malyska, Nicola Sahar +3
Machine Learning (ML) is widely used to automatically extract meaningful information from Electronic Health Records (EHR) to support operational, clinical, and financial decision-m…
Using Molecular Embeddings in QSAR Modeling: Does it Make a Difference?
María Virginia Sabando, Ignacio Ponzoni, Evangelos E. Milios +1
With the consolidation of deep learning in drug discovery, several novel algorithms for learning molecular representations have been proposed. Despite the interest of the community…
COVID-19 Pandemic: Identifying Key Issues using Social Media and Natural Language Processing
Oladapo Oyebode, Chinenye Ndulue, Dinesh Mulchandani +6
The COVID-19 pandemic has affected people's lives in many ways. Social media data can reveal public perceptions and experience with respect to the pandemic, and also reveal factors…
Detecting Ongoing Events Using Contextual Word and Sentence Embeddings
Mariano Maisonnave, Fernando Delbianco, Fernando Tohmé +2
This paper introduces the Ongoing Event Detection (OED) task, which is a specific Event Detection task where the goal is to detect ongoing event mentions only, as opposed to histor…
Enhancement of Short Text Clustering by Iterative Classification
Md Rashadul Hasan Rakib, Norbert Zeh, Magdalena Jankowska +1
Short text clustering is a challenging task due to the lack of signal contained in such short texts. In this work, we propose iterative classification as a method to b o ost the cl…
Vector Embedding of Wikipedia Concepts and Entities
Ehsan Sherkat, Evangelos Milios
Using deep learning for different machine learning tasks such as image classification and word embedding has recently gained many attentions. Its appealing performance reported acr…
Statistical Learning for OCR Text Correction
Jie Mei, Aminul Islam, Yajing Wu +2
The accuracy of Optical Character Recognition (OCR) is crucial to the success of subsequent applications used in text analyzing pipeline. Recent models of OCR post-processing signi…
Event Evolution Tracking from Streaming Social Posts
Pei Lee, Laks V. S. Lakshmanan, Evangelos E. Milios
Online social post streams such as Twitter timelines and forum discussions have emerged as important channels for information dissemination. They are noisy, informal, and surge qui…