1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Edu-Theater: A Data-Efficient Agent Framework for Scalable Learner Behavior Simulation through Staging Roll-Call
Weibo Gao, Qi Liu, Linan Yue +6
Large-scale learner-task interaction data are crucial for intelligent educational systems but are costly to collect and constrained by privacy and learner engagement. Learner simul…
cs.CL2026
LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services
Jinwen Chen, Shiwen Zhang, Shuai Gong +6
In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage systems rely heavily on historica…
cs.CL2024★ 1 cited
Mitigating Training Imbalance in LLM Fine-Tuning via Selective Parameter Merging
Yiming Ju, Ziyi Ni, Xingrun Xing +4
Supervised fine-tuning (SFT) is crucial for adapting Large Language Models (LLMs) to specific tasks. In this work, we demonstrate that the order of training data can lead to signif…