Improving Instruct Models for Free: A Study on Partial Adaptation (2025.emnlp-main)
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Ozan Irsoy, Pengxiang Cheng, Jennifer L Chen, Daniel Preotiuc-Pietro, Shiyue Zhang, Duccio Pappadopulo
| Challenge: | Instruct models are deemed superior and more usable but can be eroded by instruction tuning . a recent study shows that instruct models are better at following instructions than base models . |
| Approach: | They scale down the strength of instruction tuning to improve model performance . they show that reducing instruction tuning results in material improvement . |
| Outcome: | The proposed model improves on a few-shot in-context learning benchmark . but it loses some degree of its in-training ability . |
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