5 papers
Machine Unlearning for Class Removal through SISA-based Deep Neural Network Architectures
Ishrak Hamim Mahi, Siam Ferdous, Md Sakib Sadman Badhon +4
The rapid proliferation of image generation models and other artificial intelligence (AI) systems has intensified concerns regarding data privacy and user consent. As the availabil…
Exploring the Limits of Pruning: Task-Specific Neurons, Model Collapse, and Recovery in Task-Specific Large Language Models
M. K. Khalidi Siam, Md. Tausif-Ul-Islam, Md. Reshad Romim Khan +5
Neuron pruning is widely used to reduce the computational cost and parameter footprint of large language models, yet it remains unclear whether neurons in task-specific models cont…
Enhancing Mental Health Counseling Support in Bangladesh using Culturally-Grounded Knowledge
Md Arid Hasan, Azhagu Meena SP, Aditya Khan +6
Large language models (LLMs) show promise in generating supportive responses for mental health and counseling applications. However, their responses often lack cultural sensitivity…
Reliability Gated Multi-Teacher Distillation for Low Resource Abstractive Summarization
Dipto Sumit, Ankan Kumar Roy, Sadia Khair Rodela +4
We study multiteacher knowledge distillation for low resource abstractive summarization from a reliability aware perspective. We introduce EWAD (Entropy Weighted Agreement Aware Di…
Benchmarking Bengali Dialectal Bias: A Multi-Stage Framework Integrating RAG-Based Translation and Human-Augmented RLAIF
K. M. Jubair Sami, Dipto Sumit, Ariyan Hossain +1
Large language models (LLMs) frequently exhibit performance biases against regional dialects of low-resource languages. However, frameworks to quantify these disparities remain sca…