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Starts 8 June 2025 06:14
Ends 8 June 2025
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Hallucinations, Prompt Manipulations, and Mitigating Risk: Putting Guardrails around your LLM-Powered Applications
Discover effective strategies for mitigating LLM risks through guardrails, including pre-processing techniques against prompt manipulation, output evaluation methods, and open-source frameworks demonstrated in real-world applications.
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Overview
Discover effective strategies for mitigating LLM risks through guardrails, including pre-processing techniques against prompt manipulation, output evaluation methods, and open-source frameworks demonstrated in real-world applications.
Syllabus
- Introduction to LLM Risks
- Understanding Prompt Manipulations
- Pre-processing Techniques
- Output Evaluation Methods
- Implementing Guardrails
- Open-Source Frameworks for LLM Guardrails
- Case Studies and Real-World Applications
- Mitigating Risk in Dynamic Environments
- Closing Remarks
Overview of hallucinations and prompt manipulations
Importance of guardrails in LLM applications
Types of prompt manipulation techniques
Impact on output quality and reliability
Input validation and sanitization
Contextual awareness and prompt structuring
Automated evaluation metrics
Human-in-the-loop feedback systems
Role of safety layers and filters
Balancing creativity with control
Overview of available tools and libraries
Integration with real-world applications
Successful implementation examples
Lessons learned and best practices
Continuous monitoring and updating guardrails
Adaptive strategies for evolving threats
Summary of strategies and tools
Future directions and emerging technologies in LLM safety
Subjects
Computer Science
