In the news
CordisBench: Can Language Models Reason About Component Lifecycles in Dynamic Agent Harnesses?
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- CordisBench, a 1,200-question benchmark, tests whether language models can reason about component lifecycles in dynamic agent systems that manage dependencies and cleanup.
- Why it matters
- Matters for engineers building AI agents that modify their own execution environment or manage complex plugin and dependency systems at runtime.
- Watch out
- Models degrade significantly as system complexity grows; reasoning costs are high, with GPT-5.6 Luna using nearly 3,000 tokens per question at medium effort.
- agent
- language model
- reasoning
- benchmark
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