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Found 4 papers, 1 papers with code
AI Risk Management Should Incorporate Both Safety and Security
The exposure of security vulnerabilities in safety-aligned language models, e. g., susceptibility to adversarial attacks, has shed light on the intricate interplay between AI safety and AI security.
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
We develop methods to identify critical regions that are vital for safety guardrails, and that are disentangled from utility-relevant regions at both the neuron and rank levels.
IDO-VFI: Identifying Dynamics via Optical Flow Guidance for Video Frame Interpolation with Events
The proposed method first estimates the optical flow based on frames and events, and then decides whether to further calculate the residual optical flow in those sub-regions via a Gumbel gating module according to the optical flow amplitude.
Hardware Acceleration of Sampling Algorithms in Sample and Aggregate Graph Neural Networks
Sampling is an important process in many GNN structures in order to train larger datasets with a smaller computational complexity.
