2 papers
cs.LG2026
Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data
Antonio Pelusi, Stefano Braghin, Alberto Trombetta
Large language models (LLMs) are increasingly used as conditional generators for structured data, relying on in-context learning (ICL) to adapt to new distributions without paramet…
cs.CR2026
On-line Anomaly Detection and Qualification of Random Bit Streams
Cesare Gerolimetto Fabrello, Valeria Rossi, Kamil Witek +2
Generating random bit streams is required in various applications, most notably cyber-security. Ensuring high-quality and robust randomness is crucial to mitigate risks associated…