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Jiaxin Pei

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#artificial intelligence Review Sep 2026

Relic: From Multi-Agent Collaboration to Persistent Organizational Capability

Multiple agents may often conflict in an organization: for example, one coding agent changes an interface in a repository, but another continues to develop on the old version where existing tests become stale. A conversation can resolve the episode, but when the participants change, what makes the lesson continue to go...

Hong-Yi Du, Tian-Yi Zhang, Wei-Jia Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

AI Should Facilitate Democratic Deliberation at Scale

AI systems can strengthen democracy by supporting deliberation at scale by addressing cognitive, social, platform-design, and market-driven frictions, while preserving human agency. Unlike proposals such as liquid democracy that restructure representation through vote delegation, in this position paper, we argue that A...

José Ramón Enríquez, Jia-Xin Pei, A. Pentland · 0 citations
Review Jul 2026

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are rarely disclosed to the public or regulators, creating a serious trust and accountability gap in the wide deployment of AI systems. In this p...

Xiangning Lin, Shenzhe Zhu, Shu Yang et al. · 0 citations
Preprint Jul 2026

ChainSWE: Benchmarking Coding Agents on Multi-Bug Software Maintenance

ChainSWE is introduced, the first benchmark for evaluating agents on sequential, dependent bug fixes within a shared codebase, and reveals a consistent performance drop by up to 70% as the chain length increases.

Qirui Jin, Lingching Tung, Kenan Li et al. · 1 citation · ⚡1

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