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arXiv AI By Ching-Chun Chang, Yuchen Guo, Hanrui Wang, Timo Spinde, Isao Echizen

Role-Aware Artificial Intelligence Across Augmentation and Automation in Human-Machine Symbiosis

Read the original on arXiv AI →

The paper explores how to trace the functional role of AI in natural language generation, distinguishing between AI acting as an assistive editor or a creative generator. It proposes a methodology that infers the latent role from prompts, embeds it during generation, and recovers the role from the output. Experiments demonstrate that the approach can discriminate roles, remains robust to perturbations, and preserves linguistic quality.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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