NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs

Multimodal expansion of large language models (LLMs) enables new perceptual capabilities but often compromises the language intelligence acquired during pretraining. In this work, we investigate this phenomenon from the perspective of internal adaptation dynamics and discover that neurons in pretrained LLMs exhibit heterogeneous plasticity during multimodal learning: some neurons are critical for preserving language capabilities, while others are more adaptive to multimodal knowledge. Based on t

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ethics.ai (7 August 2026), “NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs,” evidence record 18747, https://ethics.ai/record/18747 (originally published by HuggingFace Daily Papers).

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