Creativity, honesty and designed forgetting emerge in small hyperbolic language models
Language models are optimised for scale, yet remain functional rather than companionable, and as an assistant personalises into a companion, accumulating memory of one user, it quietly becomes someone, and can silently acquire traits that harm that user. What a companion is becoming, and what would make it worth becoming, has no reliable instrument: trained human raters cannot agree on the answer (Fleiss kappa = 0.074). Here we show that three small language models (146 M to 3 B parameters) sharing a hyperbolic substrate answer both halves of that question. A 146 M behavioural auditor, trained
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- Linked via arxiv authorKwan Soo Shin →
Creativity, honesty and designed forgetting emerge in small hyperbolic language models
- Linked via arxiv authorIn Seok Kang →
Creativity, honesty and designed forgetting emerge in small hyperbolic language models
- Linked via arxiv authorYunkyung Min →
Creativity, honesty and designed forgetting emerge in small hyperbolic language models
