Ada

When would you need the offset_mapping feature that HuggingFace fast tokenizers provide?

Why string match accuracy fails as an LLM evaluation metric

How does DSPy reframe prompt engineering and what does it gain over hand written prompts?

Explain the difference between self-attention and cross-attention. When does each appear in a real architecture?

How should an agent recover when the previous turn produced output that failed schema validation?

Which quality dimension is uniquely challenging about multi turn dialog evaluation vs single turn?

How does Reflexion let an agent improve across failed attempts without updating model weights?

What data shape does a tool calling fine-tune use, and what commonly goes wrong?

The model provider just updated the model behind the API endpoint. Describe the regression testing process before allowing traffic.

Before the tokenizer even starts splitting, normalization runs. What does it do and why?