Publications
Conference Papers
ClaimIQ at CheckThat! 2025: Comparing Prompted and Fine-Tuned Language Models for Verifying Numerical Claims
Anirban Saha Anik, Md Fahimul Kabir Chowdhury, Andrew Wyckoff, Sagnik Ray Choudhury
Working Notes of the Conference and Labs of the Evaluation Forum, 2025
We compare prompted and fine-tuned language models for verifying numerical claims in the CheckThat! Lab Task 3 challenge, demonstrating effective approaches for claim verification.
A Dynamic Fusion Model for Consistent Crisis Response
Xiaoying Song, Anirban Saha Anik, Eduardo Blanco, Vanessa Frías-Martínez, and Lingzi Hong
The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025 Findings), 2025
We introduce a dynamic fusion framework that integrates multiple LLMs to generate consistent, high-quality crisis responses across professionalism, actionability, and relevance dimensions.
Speaking at the Right Level: Literacy-Controlled Counterspeech Generation with RAG-RL
Xiaoying Song, Anirban Saha Anik, Dibakar Barua, Pengcheng Luo, Junhua Ding, and Lingzi Hong
The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025 Findings) – Accepted, 2025
We propose a Controlled-Literacy framework that integrates Retrieval-Augmented Generation (RAG) and Reinforcement Learning (RL) to generate counterspeech tailored to different health literacy levels.
[🏆 Finalist, SIG-SM Social Media Research Competition 2025]
Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation
Anirban Saha Anik, Xiaoying Song, Elliott Wang, Bryan Wang, Bengisu Yarimbas, and Lingzi Hong
Second Conference on Language Modeling, 2025
A multi-agent LLM framework that generates evidence-based counterspeech grounded in dynamic and static retrieval sources, achieving significant improvements over RAG baselines.
[🏆 Runner-Up, SIG-SM Social Media Research Competition 2025]
Dynamic Fusion of Large Language Models for Crisis Communication
Xiaoying Song, Anirban Saha Anik, Vanessa Frías-Martínez, and Lingzi Hong
International Conference on Information Systems for Crisis Response and Management, 2025
We propose a dynamic fusion framework using multiple LLMs to generate high-quality, real-time responses in crisis scenarios on social media.
A Hybrid Attention-Guided Fusion Network with Grad-CAM for MPox Skin Lesion Classification
Mithila Arman, Naheyan Prottush, Maher Ali Rusho, Arup Datta, Anirban Saha Anik, Din Mohammad Dohan, Md. Ashiq Ul Islam Sajid, Intezab Alam Sheikh, Md. Khurshid Jahan
2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI), 2025
A hybrid attention-guided fusion network using Grad-CAM for classifying MPox skin lesions with improved interpretability and diagnostic accuracy.
Outcome-Based Education: Evaluating Students' Perspectives Using Transformer
Shuvra Smaran Das, Anirban Saha Anik, Md. Kishor Morol, and Mohammad Sakib Mahmood
27th International Conference on Computer and Information Technology, 2024
Evaluating students perspectives on outcome-based education using transformer-based natural language processing to analyze educational feedback and sentiments.
A Study on Future Lockdown Predictions Using ANN
Shuvra Smaran Das, Anirban Saha Anik, Md. Muzakker Hossain, Md. Kishor Morol, Fariha Jahan, Md. Abdullah Al-Jubair
International Conference on Next-Generation Computing, IoT and Machine Learning, 2023
A study using artificial neural networks to predict future lockdown scenarios during the COVID-19 pandemic based on epidemiological and social data.
A Comparative Analysis for the Detection of COVID-19 from Chest X-ray Dataset
Anirban Saha Anik, Kowshik Chakraborty, Bishowjit Datta, Abdul Kader, MD. Kishor Morol
International Conference on Recent Progresses in Science, Engineering and Technology, 2022
A comprehensive comparative analysis of deep learning methods for detecting COVID-19 from chest X-ray images, evaluating multiple CNN architectures.