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Found 5 papers, 2 papers with code
TeleChat Technical Report
Subsequently, the model undergoes fine-tuning to align with human preferences, following a detailed methodology that we describe.
Masked Language Model Based Textual Adversarial Example Detection
To explore how to use the masked language model in adversarial detection, we propose a novel textual adversarial example detection method, namely Masked Language Model-based Detection (MLMD), which can produce clearly distinguishable signals between normal examples and adversarial examples by exploring the changes in manifolds induced by the masked language model.
Evaluating Membership Inference Through Adversarial Robustness
The usage of deep learning is being escalated in many applications.
Self-Supervised Adversarial Example Detection by Disentangled Representation
To alleviate this problem, we explore how to detect adversarial examples with disentangled label/semantic features under the autoencoder structure.
The Modeling of SDL Aiming at Knowledge Acquisition in Automatic Driving
In this paper we proposed an ultimate theory to solve the multi-target control problem through its introduction to the machine learning framework in automatic driving, which explored the implementation of excellent drivers' knowledge acquisition.
