3 papers
cs.CL2026
Compressing Language Models for Specialized Domains
Miles Williams, George Chrysostomou, Vitor Jeronymo +1
Language models (LMs) excel at tasks across diverse domains, yet require substantial computational resources during inference. Compression techniques such as pruning and quantizati…
cs.CL2025
Self-calibration for Language Model Quantization and Pruning
Miles Williams, George Chrysostomou, Nikolaos Aletras
Quantization and pruning are fundamental approaches for model compression, enabling efficient inference for language models. In a post-training setting, state-of-the-art quantizati…
cs.CL2024
Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization
George Chrysostomou, Zhixue Zhao, Miles Williams +1
Despite the remarkable performance of generative large language models (LLMs) on abstractive summarization, they face two significant challenges: their considerable size and tenden…