5 papers
Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation
Zhiwei Zhang, Zechen Sun, Fei Zhao +6
On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher on the student's own rollouts. Vanilla OPD applies this supe…
D-MOPD: Adaptive Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation
Zechen Sun, Zhiwei Zhang, Fei Zhao +7
Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence on the student's own rollou…
QP-OneModel: A Unified Generative LLM for Multi-Task Query Understanding in Xiaohongshu Search
Jianzhao Huang, Xiaorui Huang, Fei Zhao +9
Query Processing (QP) bridges user intent and content supply in large-scale Social Network Service (SNS) search engines. Traditional QP systems rely on pipelines of isolated discri…
Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training
Shengrui Li, Fei Zhao, Kaiyan Zhao +6
Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence with proficiency on hard tasks such a…
Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors
Zhiwei Zhang, Fei Zhao, Rui Wang +6
Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models often fall into repetitive invalid…