Papers with **Parametric Skill Transfer
Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation (2026.acl-long)
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| Challenge: | Large Language Models face the "knowledge cutoff" problem because their parametric memory remains frozen after pretraining, preventing them from natively internalizing new information or tools on the fly. |
| Approach: | They propose a framework that supports modular skill transfer for efficient and effective knowledge adaptation by extracting a domain-agnostic **Skill Vector from a source domain. |
| Outcome: | Experiments on knowledge-incorporation QA (SQuAD, LooGLE) and agentic tool-use benchmarks show that the proposed framework outperforms state-of-the-art self-editing SFT by 9.9 points. |