Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing
Long-context adaptation is often viewed as window scaling, but this misses a token-level supervision mismatch: in packed training with document masking, each target token's effective context remains short. We introduce EXACT, a supervision-allocation objective that assigns extra weight to long effective-context targets by inverse frequency within the long tail. Across seven Qwen/LLaMA CPT configurations, EXACT improves all 28 trained/extrapolated NoLiMa and RULER comparisons. On Qwen2.5-0.5B, NoLiMa improves by +10.09 (trained) and +5.34 (extrapolated); RULER by +10.69 and +5.55. On LLaMA-3.2-3B, RULER improves by +17.91 and +16.11. Standard QA/reasoning are preserved (+0.24 macro change ...
| Authors | Jinchang Zhu, Jindong Li, Chengyu Zou et al. |
|---|---|
| Primary category | cs.CL |
| Published | 11 May 2026 |
| Last updated at source | 29 August 2026 |
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