Tag: adversarial machine learning
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In-Context Fixation: Impact of Labels on Few-Shot AI Learning
Explore how demonstrated labels affect few-shot classification accuracy and why label diversity matters in in-context learning for AI models.
MS-FLOW: Sparse Bottleneck for Accurate Multivariate Forecasting
Discover MS-FLOW, a novel sparse bottleneck framework enhancing multivariate forecasting accuracy by modeling effective cross-variable dependencies.
Multi-Armed Bandits: Best-Action Queries Boost Learning
Discover how best-action queries improve multi-armed bandit models, reducing regret and enhancing decision-making in AI and machine learning.
Efficient Prompt Learning for Accurate Traffic Forecasting
Discover SimpleST, a lightweight prompt tuning framework that boosts spatio-temporal GNNs for precise and efficient urban traffic forecasting.
PolyLM: Predicting Polymer Physics from Synthesis Text
Discover how PolyLM uses large language models to predict polymer properties by analyzing synthesis and processing descriptions in scientific literature.