arXiv cs.AIPaper
Everything in Moderation: Per-Domain Coverage Optima and Alignment-Resistant Domain Gaps in Multi-Domain Mid-Training
This is careful empirical work on a real problem: how much of each domain should you train on before alignment? The finding that moderate coverage is best for all domains is useful, but it's domain-specific to logical reasoning on KOR-Bench. The second finding, that alignment can't fully undo mid-training allocation choices, is more consequential: it means those decisions get locked in. Relevant if you're doing multi-domain mid-training, otherwise academic.