Research

Transparent Screening for LLM Inference and Training Impacts

Researchers propose a screening framework to quantify and make transparent the computational and environmental impacts of LLMs during both training and inference phases.

Thursday, April 23, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline

Appears to be a machine learning research paper addressing transparency and impact assessment for large language models across both inference and training phases.

Read original at arXiv CS.LG (Machine Learning)

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