28 citations · 82 across the 33 of their papers we have counts for
36 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…
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…
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…
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…
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…
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…
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…
PRKAN: Parameter-Reduced Kolmogorov-Arnold Networks
Hoang-Thang Ta, Duy-Quy Thai, Anh Tran +2
Kolmogorov-Arnold Networks (KANs) represent an innovation in neural network architectures, offering a compelling alternative to Multi-Layer Perceptrons (MLPs) in models such as Con…
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…
Social Support Detection from Social Media Texts
Zahra Ahani, Moein Shahiki Tash, Fazlourrahman Balouchzahi +3
Social support, conveyed through a multitude of interactions and platforms such as social media, plays a pivotal role in fostering a sense of belonging, aiding resilience in the fa…
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…
FC-KAN: Function Combinations in Kolmogorov-Arnold Networks
Hoang-Thang Ta, Duy-Quy Thai, Abu Bakar Siddiqur Rahman +2
In this paper, we introduce FC-KAN, a Kolmogorov-Arnold Network (KAN) that leverages combinations of popular mathematical functions such as B-splines, wavelets, and radial basis fu…
A multitask learning framework for leveraging subjectivity of annotators to identify misogyny
Jason Angel, Segun Taofeek Aroyehun, Grigori Sidorov +1
Identifying misogyny using artificial intelligence is a form of combating online toxicity against women. However, the subjective nature of interpreting misogyny poses a significant…
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…
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents
Hoang-Thang Ta, Abu Bakar Siddiqur Rahman, Lotfollah Najjar +1
This paper describes our participation in Task 3 and Task 5 of the #SMM4H (Social Media Mining for Health) 2024 Workshop, explicitly targeting the classification challenges within…
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…
GuReT: Distinguishing Guilt and Regret related Text
Sabur Butt, Fazlourrahman Balouchzahi, Abdul Gafar Manuel Meque +4
The intricate relationship between human decision-making and emotions, particularly guilt and regret, has significant implications on behavior and well-being. Yet, these emotions s…
Leveraging the power of transformers for guilt detection in text
Abdul Gafar Manuel Meque, Jason Angel, Grigori Sidorov +1
In recent years, language models and deep learning techniques have revolutionized natural language processing tasks, including emotion detection. However, the specific emotion of g…
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models
Atnafu Lambebo Tonja, Hellina Hailu Nigatu, Olga Kolesnikova +3
This paper describes CIC NLP's submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas. We present the system descrip…
Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec
Atnafu Lambebo Tonja, Christian Maldonado-Sifuentes, David Alejandro Mendoza Castillo +4
In this paper, we present a parallel Spanish-Mazatec and Spanish-Mixtec corpus for machine translation (MT) tasks, where Mazatec and Mixtec are two indigenous Mexican languages. We…
Transformer-based approaches to Sentiment Detection
Olumide Ebenezer Ojo, Hoang Thang Ta, Alexander Gelbukh +3
The use of transfer learning methods is largely responsible for the present breakthrough in Natural Learning Processing (NLP) tasks across multiple domains. In order to solve the p…
Guilt Detection in Text: A Step Towards Understanding Complex Emotions
Abdul Gafar Manuel Meque, Nisar Hussain, Grigori Sidorov +1
We introduce a novel Natural Language Processing (NLP) task called Guilt detection, which focuses on detecting guilt in text. We identify guilt as a complex and vital emotion that…
ReDDIT: Regret Detection and Domain Identification from Text
Fazlourrahman Balouchzahi, Sabur Butt, Grigori Sidorov +1
In this paper, we present a study of regret and its expression on social media platforms. Specifically, we present a novel dataset of Reddit texts that have been classified into th…