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Found 6 papers, 4 papers with code
PID Control-Based Self-Healing to Improve the Robustness of Large Language Models
This approach reduces the computational cost to that of using just the P controller, instead of the full PID control.
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs
The unique capabilities of Large Language Models (LLMs), such as the natural language text generation ability, position them as strong candidates for providing explanation for recommendations.
Asymptotically Fair Participation in Machine Learning Models: an Optimal Control Perspective
Moreover, we design a surrogate retention system based on existing literature on evolutionary population dynamics to approximate the dynamics of distribution shifts on active user counts, from which the objective of achieving asymptotically fair participation is formulated as an optimal control problem, and the control variables are considered as the model parameters.
Contrastive Learning with Consistent Representations
Addressing this challenge and facilitating the systematic incorporation of diverse data augmentations, this paper proposes Contrastive Learning with Consistent Representations CoCor.
Self-Healing Robust Neural Networks via Closed-Loop Control
While numerous attack and defense techniques have been developed, this work investigates the robustness issue from a new angle: can we design a self-healing neural network that can automatically detect and fix the vulnerability issue by itself?
Towards Robust Neural Networks via Close-loop Control
We connect the robustness of neural networks with optimal control using the geometrical information of underlying data to design the control objective.
