4 papers · 1 filter
MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs
Saman Sarker Joy, Niloy Farhan
Large language models (LLMs) are increasingly used for health-related advice. Existing research measures their safety with static questions rather than pressured patient-facing con…
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…
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…
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…