# open-weight
標記為「open-weight」的 14 篇文章
Case Study: DeepSeek Model Safety Evaluation Findings
Comprehensive analysis of safety evaluation findings for DeepSeek models, including comparative assessments against GPT-4 and Claude, jailbreak susceptibility testing, and implications for open-weight model deployment.
Gemma Security Deep Dive
Comprehensive security analysis of Google's Gemma open-weight models including safety training effectiveness and fine-tuning attack surfaces.
Llama 4 Security Analysis
Security analysis of Llama 4 including open-weight attack surface and fine-tuning vulnerabilities.
Emerging Models
Security analysis of emerging open-weight models including DeepSeek, Qwen, and Command R+, covering new attack surfaces, less-tested safety measures, and multilingual exploitation techniques.
Open-Weight Model Security
Security analysis of open-weight models including Llama, Mistral, Qwen, and DeepSeek, covering unique risks from full weight access, fine-tuning attacks, and deployment security challenges.
Mistral & Mixtral
Security analysis of Mistral and Mixtral models, including Mixture of Experts exploitation, sparse activation attacks, minimal safety alignment implications, and open-weight deployment risks.
Open Weight vs API Security Comparison
Comparative analysis of security properties between open-weight deployments and API-based access, including unique attack surfaces for each.
Case Study: DeepSeek 模型 Safety Evaluation Findings
Comprehensive analysis of safety evaluation findings for DeepSeek models, including comparative assessments against GPT-4 and Claude, jailbreak susceptibility testing, and implications for open-weight model deployment.
Gemma 安全 Deep Dive
Comprehensive security analysis of Google's Gemma open-weight models including safety training effectiveness and fine-tuning attack surfaces.
Llama 4 安全 Analysis
安全 analysis of Llama 4 including open-weight attack surface and fine-tuning vulnerabilities.
新興模型
新興開放權重模型（含 DeepSeek、Qwen 與 Command R+）之安全分析，涵蓋新攻擊面、較少測試之安全措施與多語言利用技術。
開源權重模型安全
開源權重模型（包括 Llama、Mistral、Qwen 與 DeepSeek）之安全分析，涵蓋自完整權重存取、微調攻擊，與部署安全挑戰之獨特風險。
Mistral 與 Mixtral
Mistral 與 Mixtral 模型之安全分析，包括 Mixture of Experts 攻擊、稀疏啟動攻擊、最小化安全對齊之意涵，以及開源權重部署風險。
Open Weight vs API 安全 Comparison
Comparative analysis of security properties between open-weight deployments and API-based access, including unique attack surfaces for each.