Tag: adversarial machine learning
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Language Models Detect Dropout and Gaussian Noise Accurately
Discover how advanced language models identify and differentiate dropout and Gaussian noise in activations, enhancing AI robustness and safety.
Semantic Gradient Descent: Optimizing SLM Harnesses
Discover how Semantic Gradient Descent improves Semantic Language Models with deterministic workflows, boosting accuracy and efficiency in AI deployments.
Mastering Liar’s Poker with AI: Outbluffing Elite Humans
Discover how AI agent Solly uses self-play and reinforcement learning to master Liar's Poker, outperforming top human players with innovative bluffing stra...
Training-Free Time Series Classification with LLM Agents
Discover FETA, a training-free framework using LLM agents for accurate, efficient time series classification without labeled data or pretraining.
Controllable Hypothesis Generation for Abductive Reasoning
Explore CtrlHGen, a novel framework for controllable logical hypothesis generation improving abductive reasoning in knowledge graphs.