arXiv — cs.AI preprintsInternational21 October 2026
Knowledge That Is Linear Before Fine-Tuning Generalizes After It
This is an official announcement record
Firsthand records what arXiv — cs.AI preprints announced and links to the original. The wording below is theirs, not ours.
arXiv:2610.22300v2 Announce Type: replace-cross Abstract: Not all facts a language model can recall support further learning equally well. We distinguish active facts, which support generalization beyond their own recall, from inert facts, which can be recalled but do not support such generalization in a given task. We study this distinction by constructing new relations from existing ones. Take the relation that maps a place to its continent (Paris -> Europe) and assign each of its answers an arbitrary new label (Europe -> crab, Asia -> zebra). The new relation then maps Paris -> crab. We fin
Read the official announcement
Opens arxiv.org
More from arXiv — cs.AI preprints
- Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training21 October 2026
- Large language model and reinforcement learning based autonomous construction and progress updates21 October 2026
- Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models21 October 2026
- MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring21 October 2026
- DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution21 October 2026
This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.