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.
RakutenAI-7B: Extending large language models for Japanese
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
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Proposes a privacy-preserving RAG system using LLMs and syllabus data for academic advising on course sequences and personalized planning.
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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A Locally Deployed RAG-Based Academic Advising System for Course Selection
Proposes a privacy-preserving RAG system using LLMs and syllabus data for academic advising on course sequences and personalized planning.