Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
EvoGenUI-Bench: Evaluating LLMs as Multi-Turn Generative UI Assistants
Yue Peng, Lanke Xia, Zihan Wang +3
Large language models can generate interactive web interfaces, but reliable generative UI requires maintaining an executable artifact as user requests evolve. We introduce EvoGenUI…
cs.AI2026
Toward Latent Language Model Skills Steering and Optimization: An Empirical Study
Xunyi Jiang, Junda Wu, Yuxin Xiong +6
Skills, as a useful abstraction for the procedural capabilities of large language models (LLMs), capture how models perform structured, multi-step reasoning and program execution.…
cs.AI2026
NovelAPIBench: Diagnosing How A Code LLM Learns to Use Novel APIs
Jinnuo Liu, Yue Peng, Jinhan Niu +1
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…