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Dyad: Extending Large Language Models with Native Typed Decision-Making

Yundaichuan Zhan, Weishi Wang, Wenbiao Liu وآخرون · 2026

We study how to build more capable general-purpose agents by extending large language models (LLMs) with native typed decision-making. We introduce Dyad, an architecture that augments a pretrained LLM with an environment-conditioned action encoder that embeds each candidate action description in parallel, then scores t …

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How Far Do Persona Effects Generalize in Language Models?

Persona prompts ask language models to answer as particular kinds of people. We test whether relationships learned from these effects predict responses to new questions and remain useful across models and prompts. Across 57 attributes, three behavioral domains, and seven pairs of open 7 to 9B checkpoints, persona effec …

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