AI RESEARCH
For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs
arXiv CS.CL
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ArXi:2508.10180v3 Announce Type: replace Data valuation is essential for enhancing the transparency and accountability of large language models (LLMs) and vision-language models (VLMs). However, existing methods typically rely on gradient computations, making them computationally prohibitive for billion-parameter models and precluding batch parallelization. In this work, we