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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...
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...
A user-centric framework for systematically auditing system prompts in AI systems, AISPA is introduced, a user-centric framework for systematically auditing system prompts in AI systems that examines specific parts of a system prompt and evaluates them along eight dimensions that matter to users.
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.
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