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While modern AI detectors identify who wrote the words, emerging policies on AI use increasingly hinge on a different question: who came up with the ideas? We introduce IdeaLens, a detector that identifies whether a document's ideas came from a human or AI (idea provenance), regardless of who wrote its words. To focus...
A new scaling law with separate benefit and harm terms that allows the value of an AI token to change sign while also reducing to Chinchilla in the absence of AI text is proposed.
This work evaluates Overthink on proprietary and open-source reasoning models across the FreshQA, SQuAD, and MuSR datasets, and shows that newer generations of RLMs, while showing a drastic increase in per-token cost, also exhibit up to a 2.3x increase in reasoning tokens, leaving them more vulnerable to Overthink atta...
As LLMs are increasingly used to draft publicfacing arguments, they may flatten public debate by repeatedly introducing the same polished, plausible arguments. We study argument collapse, the tendency of essays generated by different LLMs to converge to a smaller set of main arguments, sub-arguments, and paragraph-leve...
The results suggest that length generalization is a meaningful stress test for creative-writing models and a useful lens for distinguishing otherwise close models.
Initial human feedback reveals that AI-written novels contain interesting descriptions and concepts, but often fail in long-range coherence and prose quality, including conceptual repetition, distracting details, and weak dialogues.
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