NovelAPIBench: Diagnosing How A Code LLM Learns to Use Novel APIs
Rapidly evolving software libraries require coding language models to use unfamiliar APIs. Yet failed solutions alone tell us little about what API knowledge models need or how to provide it. We present NovelAPIBench, an automated diagnostic framework that builds benchmarks around the API knowledge gaps of a target model. It identifies novel APIs, generates executable coding tasks with separately controllable knowledge components, and classifies failures into six categories. The framework can be rerun as models and libraries evolve. We study 21 libraries across five domains and six backbone models, with our primary benchmark comprising 1,670 tasks covering 856 APIs. Our experiments show t...
| Authors | Jinnuo Liu, Yue Peng, Jinhan Niu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 2 June 2026 |
| Last updated at source | 28 September 2026 |
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