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Found 16 papers, 2 papers with code
Transformer-based Multi-Task Learning for Adverse Effect Mention Analysis in Tweets
This paper presents our contribution to the Social Media Mining for Health Applications Shared Task 2021.
Interpretable Identification of Cybersecurity Vulnerabilities from News Articles
Various automated processing pipelines grounded in Natural Language Processing techniques for text classification were introduced for the early identification of vulnerabilities starting from Open-Source Intelligence (OSINT) data, including news websites, blogs, and social media.
UPB at FinCausal-2020, Tasks 1 & 2: Causality Analysis in Financial Documents using Pretrained Language Models
Financial causality detection is centered on identifying connections between different assets from financial news in order to improve trading strategies.
UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers
Conspiracy theories have become a prominent and concerning aspect of online discourse, posing challenges to information integrity and societal trust.
TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)
Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic.
UPB at SemEval-2022 Task 5: Enhancing UNITER with Image Sentiment and Graph Convolutional Networks for Multimedia Automatic Misogyny Identification
In recent times, the detection of hate-speech, offensive, or abusive language in online media has become an important topic in NLP research due to the exponential growth of social media and the propagation of such messages, as well as their impact.
Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification
Our model obtains a boost of up to 2. 42% in terms of Pearson Correlation Coefficients in contrast to vanilla training techniques, when considering the CompLex from the Lexical Complexity Prediction 2021 dataset.
UPB at SemEval-2021 Task 5: Virtual Adversarial Training for Toxic Spans Detection
The real-world impact of polarization and toxicity in the online sphere marked the end of 2020 and the beginning of this year in a negative way.
UPB at SemEval-2021 Task 1: Combining Deep Learning and Hand-Crafted Features for Lexical Complexity Prediction
Our models are applicable on both subtasks and achieve good performance results, with a MAE below 0. 07 and a Person correlation of . 73 for single word identification, as well as a MAE below 0. 08 and a Person correlation of . 79 for multiple word targets.
UPB at SemEval-2021 Task 7: Adversarial Multi-Task Learning for Detecting and Rating Humor and Offense
Detecting humor is a challenging task since words might share multiple valences and, depending on the context, the same words can be even used in offensive expressions.
UPB at SemEval-2021 Task 8: Extracting Semantic Information on Measurements as Multi-Turn Question Answering
Extracting semantic information on measurements and counts is an important topic in terms of analyzing scientific discourses.
RoBERT -- A Romanian BERT Model
Deep pre-trained language models tend to become ubiquitous in the field of Natural Language Processing (NLP).
Cross-Lingual Transfer Learning for Complex Word Identification
Our aim is to provide evidence that the proposed models can learn the characteristics of complex words in a multilingual environment by relying on the CWI shared task 2018 dataset available for four different languages (i. e., English, German, Spanish, and also French).
UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT
Manipulative and misleading news have become a commodity for some online news outlets and these news have gained a significant impact on the global mindset of people.
Romanian Diacritics Restoration Using Recurrent Neural Networks
Diacritics restoration is a mandatory step for adequately processing Romanian texts, and not a trivial one, as you generally need context in order to properly restore a character.
Building a Comprehensive Romanian Knowledge Base for Drug Administration
Information on drug administration is obtained traditionally from doctors and pharmacists, as well as leaflets which provide in most cases cumbersome and hard-to-follow details.
