What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs
英文标题：What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs
arXiv:2608.00013v1 Announce Type: new Abstract: Choosing the right large language model (LLM) backbone is the most consequential decision when building a vision-language model (VLM), yet it remains fundamentally unprincipled: compute-based scaling laws fail to generalize across model families, and
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arXiv:2608.00013v1 Announce Type: new Abstract: Choosing the right large language model (LLM) backbone is the most consequential decision when building a vision-language model (VLM), yet it remains fundamentally unprincipled: compute-based scaling laws fail to generalize across model families, and
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