In the news
LLMs Don't Know What They Know: Benchmarking Temporal Self-Knowledge for Financial Backtesting
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers benchmarked LLMs' ability to accurately report what financial facts they know, finding self-reports significantly understate actual knowledge.
- Why it matters
- Matters for engineers building financial backtests or any system relying on LLM knowledge cutoffs to avoid data leakage.
- Watch out
- Models claim ignorance on facts they answer correctly, and declared dates don't reliably prevent knowledge leakage beyond stated training windows.
- llm
- language model
- prompt
- edge
- benchmark
The patterns behind this
- Temporal Knowledge Graph Memory
- Agentic Context Engineering (Evolving Playbook)
- Eval-Driven Development (Agent CI)
Each one covers how the technique works, when it earns its cost, and where it breaks.
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