15 citations · 32 across the 32 of their papers we have counts for
32 papers · 1 filter
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…
Beyond Majority Voting: Agreement-Based Clustering to Model Annotator Perspectives in Subjective NLP Tasks
Tadesse Destaw Belay, Ibrahim Said Ahmad, Idris Abdulmumin +6
Disagreement in annotation is a common phenomenon in the development of NLP datasets and serves as a valuable source of insight. While majority voting remains the dominant strategy…
Hope Speech Detection in Social Media English Corpora: Performance of Traditional and Transformer Models
Luis Ramos, Hiram Calvo, Olga Kolesnikova
The identification of hope speech has become a promised NLP task, considering the need to detect motivational expressions of agency and goal-directed behaviour on social media plat…
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…
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…
Explainable AI: XAI-Guided Context-Aware Data Augmentation
Melkamu Abay Mersha, Mesay Gemeda Yigezu, Atnafu Lambebo Tonja +4
Explainable AI (XAI) has emerged as a powerful tool for improving the performance of AI models, going beyond providing model transparency and interpretability. The scarcity of labe…
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…
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…
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…
CULEMO: Cultural Lenses on Emotion -- Benchmarking LLMs for Cross-Cultural Emotion Understanding
Tadesse Destaw Belay, Ahmed Haj Ahmed, Alvin Grissom +4
NLP research has increasingly focused on subjective tasks such as emotion analysis. However, existing emotion benchmarks suffer from two major shortcomings: (1) they largely rely o…
Online Social Support Detection in Spanish Social Media Texts
Moein Shahiki Tash, Luis Ramos, Zahra Ahani +4
The advent of social media has transformed communication, enabling individuals to share their experiences, seek support, and participate in diverse discussions. While extensive res…
Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages
Mikhail Krasitskii, Olga Kolesnikova, Liliana Chanona Hernandez +2
This study explores transformer-based models such as BERT, mBERT, and XLM-R for multi-lingual sentiment analysis across diverse linguistic structures. Key contributions include the…
Advanced Machine Learning Techniques for Social Support Detection on Social Media
Olga Kolesnikova, Moein Shahiki Tash, Zahra Ahani +3
The widespread use of social media highlights the need to understand its impact, particularly the role of online social support. This study uses a dataset focused on online social…
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
Tadesse Destaw Belay, Israel Abebe Azime, Abinew Ali Ayele +5
Large Language Models (LLMs) show promising learning and reasoning abilities. Compared to other NLP tasks, multilingual and multi-label emotion evaluation tasks are under-explored…
Stress Detection on Code-Mixed Texts in Dravidian Languages using Machine Learning
L. Ramos, M. Shahiki-Tash, Z. Ahani +3
Stress is a common feeling in daily life, but it can affect mental well-being in some situations, the development of robust detection models is imperative. This study introduces a…
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI
Mesay Gemeda Yigezu, Melkamu Abay Mersha, Girma Yohannis Bade +3
The proliferation of fake news has emerged as a significant threat to the integrity of information dissemination, particularly on social media platforms. Misinformation can spread…
Exploring Sentiment Dynamics and Predictive Behaviors in Cryptocurrency Discussions by Few-Shot Learning with Large Language Models
Moein Shahiki Tash, Zahra Ahani, Mohim Tash +2
This study performs analysis of Predictive statements, Hope speech, and Regret Detection behaviors within cryptocurrency-related discussions, leveraging advanced natural language p…
NLP Progress in Indigenous Latin American Languages
Atnafu Lambebo Tonja, Fazlourrahman Balouchzahi, Sabur Butt +4
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements. We highlight the cultural richness of these languages a…
Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price
Moein Shahiki Tash, Zahra Ahani, Olga Kolesnikova +1
This study delves into the relationship between emotional trends from X platform data and the market dynamics of well-known cryptocurrencies Cardano, Binance, Fantom, Matic, and Ri…
EthioMT: Parallel Corpus for Low-resource Ethiopian Languages
Atnafu Lambebo Tonja, Olga Kolesnikova, Alexander Gelbukh +1
Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in h…
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
Atnafu Lambebo Tonja, Israel Abebe Azime, Tadesse Destaw Belay +10
Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resour…