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Found 6 papers, 0 papers with code
Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation
The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation.
Online Evasion Attacks on Recurrent Models:The Power of Hallucinating the Future
Recurrent models are frequently being used in online tasks such as autonomous driving, and a comprehensive study of their vulnerability is called for.
Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks
Electronic Health Records (EHRs) provide a wealth of information for machine learning algorithms to predict the patient outcome from the data including diagnostic information, vital signals, lab tests, drug administration, and demographic information.
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection
Although deep neural networks have shown promising performances on various tasks, they are susceptible to incorrect predictions induced by imperceptibly small perturbations in inputs.
Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection
Yet, most of them cannot effectively defend against whitebox attacks where an adversary has a knowledge of the model and defense.
SynFuzz: Efficient Concolic Execution via Branch Condition Synthesis
Then it uses oracle-guided program synthesis to reconstruct the symbolic expression based on input-output pairs.
Cryptography and Security
