Author

Jaeho Lee

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#artificial intelligence Preprint Oct 2026

Learning to Ask: Information Acquisition for SLM-LLM Collaboration, under a budget

This work forms SLM-LLM collaboration as an information acquisition problem, under an API budget constraint, and develops a three-stage RLVR framework that learns whether to call the advisor, how to formulate useful queries, and how to integrate the collaboration into the reasoning process by jointly refining advisor i...

Yongjun Kim, Xiao-Xiao Li, Jaeho Lee · 0 citations

Preprint Jul 2026

PARTREP: Learning What to Repeat for Decoder-only LLMs

A lightweight gate is trained that predicts high-NLL tokens from early-layer hidden states, enabling token selection during mid-prefill via early exit, motivated by the hypothesis that less predictable tokens are less recoverable from surrounding context and therefore benefit more from late-position repetition.

Andikawati P Widjaja, Yongjun Kim, Hyounghun Kim et al. · 0 citations