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This work organizes 19 public benchmarks into four systemic-risk categories defined by the EU GPAI Code of Practice---CBRN, cyber offense, harmful manipulation, and loss of control---and evaluates models using harm-preserving perturbations and simulated deployment contexts.
This work introduces TurEngMix, a corpus of 5.5K noisy, naturally occurring social media posts rich in Turkish-English code-mixing, and constructs a new Turkish-English benchmark for code-mixed language identification and named entity recognition, comprising 15K expert-annotated tokens.
Research has documented LLMs'name-based bias in hiring and salary recommendations. In this paper, we instead consider a setting where LLMs generate candidate summaries for downstream assessment. In a large-scale controlled study, we analyze nearly one million resume summaries produced by 4 models under systematic race-...
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