18 citations · 18 across the 2 of their papers we have counts for
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cs.AI2025
LATTS: Locally Adaptive Test-Time Scaling
Theo Uscidda, Matthew Trager, Michael Kleinman +3
One common strategy for improving the performance of Large Language Models (LLMs) on downstream tasks involves using a \emph{verifier model} to either select the best answer from a…
cs.AI2024★ 18 cited
Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges
Qingyao Li, Lingyue Fu, Weiming Zhang +6
Online education platforms, leveraging the internet to distribute education resources, seek to provide convenient education but often fall short in real-time communication with stu…