5 papers
BioSentinel at EXIST 2026: Soft-Label Optimization with XLM-RoBERTa for Sexism Intent Classification in Memes
Chandru Munisamy, Karthikeya Raguveer, Alapan Kuila
This paper describes the BioSentinel team's participation in EXIST 2026 Task 2.2: Source Intention in Memes, part of the CLEF 2026 evaluation campaign. The task requires classifyin…
From Text to Context: An Entailment Approach for News Stakeholder Classification
Alapan Kuila, Sudeshna Sarkar
Navigating the complex landscape of news articles involves understanding the various actors or entities involved, referred to as news stakeholders. These stakeholders, ranging from…
Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies
Alapan Kuila, Sudeshna Sarkar
Sentiment analysis plays a pivotal role in understanding public opinion, particularly in the political domain where the portrayal of entities in news articles influences public per…
Analyzing Sentiment Polarity Reduction in News Presentation through Contextual Perturbation and Large Language Models
Alapan Kuila, Somnath Jena, Sudeshna Sarkar +1
In today's media landscape, where news outlets play a pivotal role in shaping public opinion, it is imperative to address the issue of sentiment manipulation within news text. News…
PESE: Event Structure Extraction using Pointer Network based Encoder-Decoder Architecture
Alapan Kuila, Sudeshan Sarkar
The task of event extraction (EE) aims to find the events and event-related argument information from the text and represent them in a structured format. Most previous works try to…