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Заголовок на английскомDecoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models
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 representations in LLMs,…
Кратко от AI: Главные тезисы
- 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 representations in LLMs,…
Decoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models
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