8 papers
When Does Knowledge Distillation Hurt? Reliability-Aware Distillation for Low-Resource Language Summarization
Dipto Sumit, Ankan Kumar Roy Srizon, Sadia Khair Rodela +4
Knowledge distillation (KD) is a standard approach for compressing sequence-to-sequence models, but its per-sample effects are rarely examined. On the BanSum Bangla summarization b…
Contaminated Collaboration: Measuring Gender Bias Transfer in LLM-Assisted Student Writing
Ariyan Hossain, Kazi Kamruzzaman Rabbi, Farig Sadeque +1
Gender bias in LLMs has been studied extensively in model outputs, with biased prompts shown to amplify stereotyped generations. Whether such bias propagates into text produced by…
Representation-Aware Unlearning via Activation Signatures: From Suppression to Entity-Signature Erasure
Syed Naveed Mahmood, Md. Rezaur Rahman Bhuiyan, Tasfia Zaman +5
Entity-level unlearning is usually evaluated by what a model says: whether it stops naming the target, refuses a query, or shifts a Truth Ratio distribution. These output-level tes…
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…