EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Aug 24·5 min read
LLM Tool Failures: Only 3 Root Causes – Value, Condition, Intent
TL;DR
Large Language Models (LLMs) often fail due to three root causes: value, condition, and intent. These failures stem from the model's inability to recognize missing information and ask relevant questions.
✦ Why It Matters
Evaluate your LLM outputs critically to ensure accuracy before approval.
Key Takeaways
- Use an external list to define what questions the model should ask.
- Ensure all required slots are filled before execution.
- Shift focus from validation to active querying of users.
- Address values, conditions, and intent explicitly to reduce errors.
How It Works
The proposed method involves creating an external checklist that specifies what the model should ask about missing information. This checklist includes slots for values, conditions, and intent, ensuring that the model queries users for necessary inputs rather than inferring them.
By doing so, the model can accurately identify unknowns and prevent incorrect executions.