2 papers
cs.DC2026
BitFlipScope: Scalable Fault Localization and Recovery for Bit-Flip Corruptions in LLMs
Muhammad Zeeshan Karamat, Sadman Saif, Christiana Chamon Garcia
Large Language Models (LLMs) deployed in practical and safety-critical settings are increasingly susceptible to bit-flip faults caused by hardware degradation, cosmic radiation, or…
cs.LG2026
Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition
Haris Khan, Sadia Asif, Shumaila Asif +2
In real-world machine learning deployments, models must be continually updated, composed, and when required, selectively undone. However, existing approaches to model merging and c…