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Baha Rababah

2 papers indexed

arxivcs.AI2026-07-18

TopoTuner: Topological Finetuning of Large Language Models

Abdulkadir Erol, Yash Mahajan, Vepaul Hariprashad, Baha Rababah, Santu Karmaker, Cuneyt G. Akcora, et al.

Full fine-tuning remains a strong way to adapt pretrained LLMs, but it updates all weights and can be expensive. LoRA reduces the number of trainable parameters, but it does not directly answer which pretrained components should be trained and which can be frozen during adaptatio…

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arxivcs.AI2026-07-09

The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs

Baha Rababah, Cuneyt Gurcan Akcora, Carson K. Leung

Post-training quantization is widely used to deploy large language models in resource-constrained settings, yet its evaluation relies almost exclusively on accuracy and perplexity. We show that these metrics fail to capture behavioral changes induced by quantization. We introduce…

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