This research paper focuses on a safety evaluation of DeepSeek-R1 and DeepSeek-V3 models within Chinese language contexts, an area previously underexplored. It highlights that while DeepSeek models possess strong reasoning capabilities, previous studies, primarily in English, have revealed significant safety flaws. To address the gap in Chinese safety assessments, the authors introduce CHiSafetyBench, a new benchmark designed to systematically test these models across various safety categories like discrimination and violation of values. The experimental results quantitatively demonstrate the deficiencies of DeepSeek models in Chinese safety performance, particularly in identifying and refusing harmful content, offering insights for future improvements. The authors acknowledge potential biases in their evaluation and plan to continually optimize the benchmark.Source: https://arxiv.org/pdf/2502.11137
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
SpaceX Said to Pursue 2026 IPO
10 Dec 2025
Bloomberg Tech
Don’t Call It a Comeback
10 Dec 2025
Motley Fool Money
Japan Claims AGI, Pentagon Adopts Gemini, and MIT Designs New Medicines
10 Dec 2025
The Daily AI Show
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
What it will take for AI to scale (energy, compute, talent)
10 Dec 2025
Azeem Azhar's Exponential View
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast