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GPT-5.4 leads LLMs in new EU digital battery passport conformance task

Researchers have introduced BatteryPass-12K, the first dataset designed for classifying digital battery passport conformance, in anticipation of the EU's upcoming battery regulation. They evaluated 22 language models, finding that GPT-5.4 achieved the highest performance in zero-shot inference. The study also revealed that few-shot examples significantly boost performance, and that scaling model parameters does not always guarantee better results, as some smaller models outperformed larger ones. Prompt-injection attacks were found to degrade model performance on this task. AI

IMPACT New dataset and model evaluations may inform development of AI for regulatory compliance in the battery sector.

RANK_REASON Academic paper introducing a new dataset and evaluating language models on a novel task.

Read on arXiv cs.CL →

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GPT-5.4 leads LLMs in new EU digital battery passport conformance task

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Tosin Adewumi, Martin Karlsson, Lama Alkhaled, Marcus Liwicki ·

    BatteryPass-12K: The First Dataset for the Novel Digital Battery Passport Conformance Task

    arXiv:2604.26986v1 Announce Type: new Abstract: We introduce a novel task of digital battery passport (DBP) conformance classification and introduce the first public benchmark for the task: BatteryPass-12K, created synthetically from real pilot samples. This is as the EU's batter…