An arXiv paper reports that fine-tuning GPT-4o, Gemini 2.5 Pro, and DeepSeek-V3.1 on summary-to-text expansion tasks increases verbatim reproduction of copyrighted books.
TRACER, a recent arXiv paper, takes the input/output logs of an LLM classification endpoint and reuses them as training data, then swaps in a lightweight surrogate only on regions that pass a parity gate to cut inference cost. The surrogate absorbs 83–100% of traffic on a 77-class intent dataset and 100% on a 150-class one, while correctly refusing to deploy on an NLI task — that refusal behavior is the interesting part.
A paper claims that a single binary operator eml(x, y) = exp(x) - ln(y) combined with the constant 1 can express all elementary functions — arithmetic, trig, logarithms, even pi. I read the paper and tested it in 5 languages.