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EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making

This story is from 2026-10-01. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.38334v2 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as agents for multi-step decision-making, yet transfer poorly to unseen environments. World-model methods address this by training agents to predict future observations, at the cost of additional…

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  1. 2026-10-01 04:00 · arXiv cs.CL
    EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making

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