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LSA-PAST: Layer-Specific Adaptation and Prototype Transport for Compositional Incremental Learning
Kyle Stein, Andrew Arash Mahyari, Guillermo Francia +2
Class-Incremental Learning (CIL) enables models to recognize new classes over time while retaining prior knowledge, but many real-world problems are compositional, where visual con…
From Task Mixtures to Specialized Experts
Hojat Allah Salehi, Mehrdad Mahdavi, Andrew Arash Mahyari +1
In collaborative foundation model fine-tuning, client data is rarely homogeneous. Instead, clients typically possess unknown mixtures of distinct data distributions, or tasks. Conv…
Adapter-Based Few-Shot Continual Learning for Malicious Packet Recognition
Kyle Stein, Guillermo Francia, III Eman El-Sheikh +1
The continual evolution of malware variants necessitates detection systems that can adapt to new threats without retraining from scratch. However, continually updating models on ne…
Curvature-Guided Module Localization for Low-Rank Detoxification of Backdoored Large Language Models
Arash Raftari, Mehrdad Mahdavi, Nathan Blackthorn +1
Backdoor attacks pose a serious threat to large language models (LLMs) by causing otherwise benign systems to produce attacker-specified malicious behavior when a hidden trigger is…