In the news
Long Text to Predictive Features: LLM-Guided Blockwise Feature Engineering via Executable Program Search
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers developed LLM-BlockFE, a framework that converts long text into executable feature programs offline, eliminating runtime LLM calls for risk-control predictions.
- Why it matters
- Matters for engineers building production risk systems that need to extract features from unstructured text without incurring per-request LLM inference costs.
- Watch out
- Results shown on two public and two private datasets; real-world deployment details and generalization to non-financial domains remain unclear from this summary.
- llm
- language model
The patterns behind this
- Process Reward Models & Verifier-Guided Search
- Eval-Driven Development (Agent CI)
- Agentic Context Engineering (Evolving Playbook)
Each one covers how the technique works, when it earns its cost, and where it breaks.
The Agent Architect
One pattern, one tradeoff, one production failure story. A short weekly briefing for people building agentic systems.
Weekly email, one-click unsubscribe. We only use your address to send the briefing.