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The Pitfalls of In-Context Learning: When Correctness Isn't Enough

In-context learning faces a surprising challenge: correct examples don't always help. New research exposes how task-preserving perturbations can undermine AI's performance.

The Mirage of Deep Learning in Anomaly Detection

Deep learning methods struggle with subtle anomalies in time series data. CoAD, a new framework, claims to bridge this gap by integrating classification and reconstruction techniques.

Decoding Quantization: The Hidden Pitfalls of Low-Bit Training