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cs.CR2026
Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks
Yi Yang, Xiaoke Chen, Jinyang Huang +6
Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very low poisoning rates, only a few…
cs.CR2026
Checkerboard: Closed-Form and Data-Independent Trigger Design for Clean-Label Backdoor Attacks
Yi Yang, Jinyang Huang, Binbin Liu +6
Backdoor attacks threaten the deep-learning supply chain by poisoning a small fraction of the training data so that a model behaves normally on clean inputs but maps triggered inpu…
cs.CL2026
Multi-Stage Evolutionary Model Merging with Meta Data Driven Curriculum Learning for Sentiment-Specialized Large Language Modeling
Keito Inoshita, Xiaokang Zhou, Akira Kawai
The emergence of large language models (LLMs) has significantly transformed natural language processing (NLP), enabling more generalized models to perform various tasks with minima…