Transfer Attacks Reveal SLM Vulnerabilities and Effective Noise Defenses | HackerNoonFlanT5-based models are more resistant to cross-model attacks, illustrating their robustness compared to other architectures.
Fine-Tuning NEO-KD for Robust Multi-Exit Networks | HackerNoonNEO-KD enhances adversarial training in multi-exit networks, improving robustness and accuracy.
A Data-centric Approach to Class-specific Bias in Image Data Augmentation: Conclusion and Limitation | HackerNoonData augmentation induces class-specific biases across various datasets, necessitating a nuanced understanding and potential architectural strategies for mitigation.