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Open access Oct 2026

Enhancing cardiovascular consultation training with a multi-agent virtual patient framework: a multi-model comparative evaluation study

Incomplete cardiovascular history-taking and suboptimal risk-factor assessment are primary contributors to delayed diagnosis and inconsistent guideline adherence. While Large Language Model (LLM)-based virtual patients (VPs) offer a scalable solution for standardized training, single-agent systems often suffer fr...

Xiao-Wei Xu, Tao Zhang, Y. Qu et al. · 0 citations
#artificial intelligence Review Oct 2026

UnityBench-Mini3D: Evaluating LLM Agents for 3D Game Development in Unity

Game development stresses coding agents in ways general software engineering does not: correctness depends on how engine APIs, serialized scene state, and runtime behavior interact, not on source code alone. Existing benchmarks mainly target platforms such as Godot and heavily rely on LLM judges or coarse task-level ou...

Yi-Jun Zhou, Ming-Hao Shao, Key Zhang et al. · 1 citation

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