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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Zhenyu Shi

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3 papers indexed here

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Review Aug 2026

PonyEval: Evaluating LLM-Based Program Repair for Capability-Safe and Actor-Oriented Pony Software

Repository-level issue-resolution benchmarks have made executable evaluation central to software-engineering agents, but their language coverage remains concentrated in mainstream ecosystems. Pony presents a different regime: it combines actors, reference capabilities, ahead-of-time compilation, and a rapidly evolving...

Bang Xie, Hao Liu, Zhen-Yu Shi et al. · 0 citations
Preprint Aug 2026

AppEval: A Unified Benchmark for LLM-Based Mobile Application Repair in ArkTS, Swift, and Kotlin

AppEval is presented, a benchmark and native-toolchain evaluation framework for mobile application repair across HarmonyOS/ArkTS, iOS/Swift, and Android/Kotlin, and shows that mobile repair performance depends strongly on the evaluated agent while demonstrating why runtime-aware acceptance is necessary for meaningful c...

Bang Xie, Hao Liu, Zhen-Yu Shi et al. · 0 citations
Review Aug 2026

OdinEval: A Reproducible Benchmark for LLM-Based Program Repair in the Odin Programming Language

OdinEval is presented, a reproducible benchmark built from documented defects in public Odin repositories built from documented defects in public Odin repositories, that evaluates six language models on 168 filtered instances under one shared protocol.

Bang Xie, Hao Liu, Zhi-Yuan Peng et al. · 0 citations

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