Papers with full-parameter fine-tuning pipeline
Compressing Language Models for Specialized Domains (2026.eacl-long)
Copied to clipboard
| Challenge: | Language models (LMs) excel at tasks across diverse domains, yet require substantial computational resources during inference. |
| Approach: | They propose a calibration method to improve the in-domain performance of compressed LMs in a post-training setting. |
| Outcome: | The proposed method outperforms existing methods on domain-specific tasks while preserving general performance. |