28 citations · 72 across the 55 of their papers we have counts for
58 papers
Why Summaries Turn Neutral: Policy Attribution for Sentiment Drift in Reinforcement Learning from Human Feedback
Mikhail Krasitskii, Alexander Gelbukh, Olga Kolesnikova +1
Reinforcement learning with human feedback (RLHF) aligns LLMs with human preferences, improving summarization fluency and safety, but causes sentiment drift: overly neutral summari…
Multiclass Sentiment Analysis for Identifying Political Viewpoints
Girma Yohannis Bade, Olga Kolesnikova, Jose Luis Oropeza +1
The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and identify different political…
Multilingual Sentiment Aware Text Summarization A Reinforcement Learning Approach for Consistency Maintenance
Mikhail Krasitskii, Alexander Gelbukh, Olga Kolesnikova +1
Reinforcement Learning from Human Feedback (RLHF) has significantly improved the quality and fluency of large language models in text summarization. However, its impact on affectiv…
Limitations of Sequence-Based Protein Representations for Parkinson's Disease Classification: A Leakage-Free Benchmark
César Jesús Núñez-Prado, Grigori Sidorov, Liliana Chanona-Hernández
The identification of reliable molecular biomarkers for Parkinson's disease remains challenging due to its multifactorial nature. Although protein sequences constitute a fundamenta…
How Psychological Learning Paradigms Shaped and Constrained Artificial Intelligence
Alex Anvi Eponon, Ildar Batyrshin, Christian E. Maldonado-Sifuentes +1
Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel configurations. This paper argues that…
Irony Detection in Urdu Text: A Comparative Study Using Machine Learning Models and Large Language Models
Fiaz Ahmad, Nisar Hussain, Amna Qasim +3
Ironic identification is a challenging task in Natural Language Processing, particularly when dealing with languages that differ in syntax and cultural context. In this work, we ai…
Fine-Tuning Large Language Models with QLoRA for Offensive Language Detection in Roman Urdu-English Code-Mixed Text
Nisar Hussain, Amna Qasim, Gull Mehak +3
The use of derogatory terms in languages that employ code mixing, such as Roman Urdu, presents challenges for Natural Language Processing systems due to unstated grammar, inconsist…
Detecting Hope Across Languages: Multiclass Classification for Positive Online Discourse
T. O. Abiola, K. D. Abiodun, O. E. Olumide +3
The detection of hopeful speech in social media has emerged as a critical task for promoting positive discourse and well-being. In this paper, we present a machine learning approac…
Multilingual Hope Speech Detection: A Comparative Study of Logistic Regression, mBERT, and XLM-RoBERTa with Active Learning
T. O. Abiola, K. D. Abiodun, O. E. Olumide +3
Hope speech language that fosters encouragement and optimism plays a vital role in promoting positive discourse online. However, its detection remains challenging, especially in mu…
Bilingual Word Level Language Identification for Omotic Languages
Mesay Gemeda Yigezu, Girma Yohannis Bade, Atnafu Lambebo Tonja +3
Language identification is the task of determining the languages for a given text. In many real world scenarios, text may contain more than one language, particularly in multilingu…
The Rise of AfricaNLP: A Survey of Contributions, Contributors, Community Impact, and Bibliometric Analysis
Tadesse Destaw Belay, Kedir Yassin Hussen, Sukairaj Hafiz Imam +11
Natural Language Processing (NLP) is undergoing constant transformation, as Large Language Models (LLMs) are driving daily breakthroughs in research and practice. In this regard, t…
SABIA: An AI-Powered Tool for Detecting Opioid-Related Behaviors on Social Media
Muhammad Ahmad, Fida Ullah, Muhammad Usman +2
Social media platforms have become valuable tools for understanding public health challenges by offering insights into patient behaviors, medication use, and mental health issues.…
Knowledge Compression via Question Generation: Enhancing Multihop Document Retrieval without Fine-tuning
Anvi Alex Eponon, Moein Shahiki-Tash, Ildar Batyrshin +3
This study presents a question-based knowledge encoding approach that improves retrieval-augmented generation (RAG) systems without requiring fine-tuning or traditional chunking. W…
Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models
Muhammad Usman, Muhammad Ahmad, M. Shahiki Tash +3
Social media platforms are critical spaces for public discourse, shaping opinions and community dynamics, yet their widespread use has amplified harmful content, particularly hate…
Hybrid Extractive Abstractive Summarization for Multilingual Sentiment Analysis
Mikhail Krasitskii, Grigori Sidorov, Olga Kolesnikova +2
We propose a hybrid approach for multilingual sentiment analysis that combines extractive and abstractive summarization to address the limitations of standalone methods. The model…
Hope Speech Detection in code-mixed Roman Urdu tweets: A Positive Turn in Natural Language Processing
Muhammad Ahmad, Muhammad Waqas, Ameer Hamza +2
Hope is a positive emotional state involving the expectation of favorable future outcomes, while hope speech refers to communication that promotes optimism, resilience, and support…
EDU-NER-2025: Named Entity Recognition in Urdu Educational Texts using XLM-RoBERTa with X (formerly Twitter)
Fida Ullah, Muhammad Ahmad, Muhammad Tayyab Zamir +4
Named Entity Recognition (NER) plays a pivotal role in various Natural Language Processing (NLP) tasks by identifying and classifying named entities (NEs) from unstructured data in…
Leveraging Large Language Models for Multi-Class and Multi-Label Detection of Drug Use and Overdose Symptoms on Social Media
Muhammad Ahmad, Fida Ullah, Muhammad Usman +3
Drug overdose remains a critical global health issue, often driven by misuse of opioids, painkillers, and psychiatric medications. Traditional research methods face limitations, wh…
GS_DravidianLangTech@2025: Women Targeted Abusive Texts Detection on Social Media
Girma Yohannis Bade, Zahra Ahani, Olga Kolesnikova +2
The increasing misuse of social media has become a concern; however, technological solutions are being developed to moderate its content effectively. This paper focuses on detectin…
Opioid Named Entity Recognition (ONER-2025) from Reddit
Muhammad Ahmad, Rita Orji, Fida Ullah +2
The opioid overdose epidemic remains a critical public health crisis, particularly in the United States, leading to significant mortality and societal costs. Social media platforms…
Multilingual Sentiment Analysis of Summarized Texts: A Cross-Language Study of Text Shortening Effects
Mikhail Krasitskii, Grigori Sidorov, Olga Kolesnikova +2
Summarization significantly impacts sentiment analysis across languages with diverse morphologies. This study examines extractive and abstractive summarization effects on sentiment…
Advancing Sentiment Analysis in Tamil-English Code-Mixed Texts: Challenges and Transformer-Based Solutions
Mikhail Krasitskii, Olga Kolesnikova, Liliana Chanona Hernandez +2
The sentiment analysis task in Tamil-English code-mixed texts has been explored using advanced transformer-based models. Challenges from grammatical inconsistencies, orthographic v…
Automated diagnosis of lung diseases using vision transformer: a comparative study on chest x-ray classification
Muhammad Ahmad, Sardar Usman, Ildar Batyrshin +5
Background: Lung disease is a significant health issue, particularly in children and elderly individuals. It often results from lung infections and is one of the leading causes of…
Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages
Tadesse Destaw Belay, Dawit Ketema Gete, Abinew Ali Ayele +4
Developing and integrating emotion-understanding models are essential for a wide range of human-computer interaction tasks, including customer feedback analysis, marketing research…