新闻
From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers consolidated 200+ internal applications onto a single self-hosted LLM by training domain-specific experts for instruction following, function-calling, and task distribution, then merging them.
- 为何重要
- Enterprise engineers managing multiple LLM deployments under data-residency constraints who want to reduce GPU fleet fragmentation and serving costs.
- 注意
- The approach trains separate models per domain then merges them, which may not generalize equally across all three axes or handle novel request patterns outside training distribution.
- llm
- rag
- post-train
- serving
- benchmark
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