Decoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models
arXiv:2609.21113v1 Announce Type: new Abstract: Fine-tuning has emerged as a widely adopted approach for adapting LLMs to a variety of downstream tasks. However, how it reshapes their internal mechanisms remains poorly understood. To address this, we investigate how fine-tuning alters internal repr…
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- 2026-09-21 04:00 · arXiv cs.AI
Decoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models