XL-SafetyBench is a new cross-cultural benchmark showing frontier LLMs decouple jailbreak robustness from cultural sensitivity while local models trade off attack success against neutral-safe rates in a near-linear pattern indicating generation failure rather than alignment.
Guerreiro, António Loison, Duarte M
3 Pith papers cite this work, alongside 8 external citations. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
CARTE is a new benchmark for fine-grained regional knowledge in France that shows LLMs exhibit performance gaps across regions and scales, pointing to uneven pretraining coverage.
A unified training framework for mesh-based ML surrogates in CFD improves accuracy and long-horizon stability by enforcing spatial derivative consistency via multi-node prediction, using temporal cross-attention correction, and adding 3D rotary positional embeddings.
citing papers explorer
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XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity
XL-SafetyBench is a new cross-cultural benchmark showing frontier LLMs decouple jailbreak robustness from cultural sensitivity while local models trade off attack success against neutral-safe rates in a near-linear pattern indicating generation failure rather than alignment.
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CARTE: A Benchmark for Mapping Language Model Knowledge Across France
CARTE is a new benchmark for fine-grained regional knowledge in France that shows LLMs exhibit performance gaps across regions and scales, pointing to uneven pretraining coverage.
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Mesh Based Simulations with Spatial and Temporal awareness
A unified training framework for mesh-based ML surrogates in CFD improves accuracy and long-horizon stability by enforcing spatial derivative consistency via multi-node prediction, using temporal cross-attention correction, and adding 3D rotary positional embeddings.