WMF-AM is a depth-parameterized benchmark that measures LLMs' cumulative state tracking ability without scratchpads, validated on 28 models across arithmetic and non-arithmetic tasks with ablations confirming the construct.
Cognitive load during problem solving: Effects on learning.Cognitive Science, 12(2):257–285, 1988
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A six-month real-world deployment of a GenAI call-taking training system produced four lessons on delivery, rigor, resilience, and human factors drawn from 98,429 user interactions and organizational data.
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WMF-AM: Probing LLM Working Memory via Depth-Parameterized Cumulative State Tracking
WMF-AM is a depth-parameterized benchmark that measures LLMs' cumulative state tracking ability without scratchpads, validated on 28 models across arithmetic and non-arithmetic tasks with ablations confirming the construct.
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Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned
A six-month real-world deployment of a GenAI call-taking training system produced four lessons on delivery, rigor, resilience, and human factors drawn from 98,429 user interactions and organizational data.