2 papers
cs.LG2026
Greedy Information Projection for LLM Data Selection
Victor Ye Dong, Kuan-Yun Lee, Jiamei Shuai +3
We present \emph{Greedy Information Projection} (\textsc{GIP}), a principled framework for choosing training examples for large language model fine-tuning. \textsc{GIP} casts selec…
cs.CL2025
DeepThink: Aligning Language Models with Domain-Specific User Intents
Yang Li, Mingxuan Luo, Yeyun Gong +4
Supervised fine-tuning with synthesized instructions has been a common practice for adapting LLMs to domain-specific QA tasks. However, the synthesized instructions deviate from re…