Cornell's Copy-Paste Language Models Boost Copying with Tiny Overhead

Cornell researchers introduced Copy-Paste Language Models (CPLM), which add a lightweight copying head that improves token copying, boosting CoT reasoning, long-context retrieval, and RAG performance with under 3% overhead.

2026-10-16 ~ 2026-10-17 · 3 related posts

• Cornell's Copy-Paste LMs add a lightweight head to boost in-context copying and long-context retrieval — lil-lab · 2026-10-16
• Copy-Paste Language Models boost CoT, long-context and RAG accuracy at under 3% overhead — yoavartzi · 2026-10-17

1 near-duplicate retellings: yoavartzi