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Found 5 papers, 2 papers with code
TANGO: Time-Reversal Latent GraphODE for Multi-Agent Dynamical Systems
Learning complex multi-agent system dynamics from data is crucial across many domains, such as in physical simulations and material modeling.
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
SAFECLIP trains on the risky data by applying unimodal CL to image and text modalities separately, and trains on the safe data using the CLIP loss.
High Probability Bounds for Stochastic Continuous Submodular Maximization
This implies that for a particular run of the algorithms, the solution may be much worse than the provided guarantee in expectation.
Robust Contrastive Language-Image Pre-training against Data Poisoning and Backdoor Attacks
In particular, ROCLIP decreases the success rate for targeted data poisoning attacks from 93. 75% to 12. 5% and that of backdoor attacks down to 0%, while improving the model's linear probe performance by 10% and maintains a similar zero shot performance compared to CLIP.
Iterative Teacher-Aware Learning
Recently, the benefits of integrating this cooperative pedagogy into machine concept learning in discrete spaces have been proved by multiple works.
