5 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Evaluating interactive agents is expensive. Agent behavior is stochastic, so reliability must be measured over repeated trials, but failures are rare and differ widely in how much they matter. Standard benchmarks spend this budget uniformly: a read-only lookup is sampled as often as an irreversible payment action. We i...
It is proved that no policy observing only a node's local view can be both safe and cost optimal, while the single classification design is both: across three environments the policy recovers the full achievable savings, 43% cheaper than restart, at 100% correctness.
A Monte Carlo study over 9837 parameter conditions (approx 9.8 million datasets) is reported and the planned-versus-achieved power gap is decompose and it is reported that treatment-correlated, outcome-dependent attrition instead induces bias, not just power loss.
A multi-agent AI system that automates competitive visibility measurement and root cause diagnosis in LLM-mediated ecommerce and introduces Agentic Share-of-Search (ASoS) as the decision target, deploys query agents across leading AI platforms, and uses a ReAct-based diagnostic agent to recommend prioritized merchandis...
Retail intelligence often relies on monitoring popular, high-velocity products, potentially biasing economic indicators by ignoring the"long tail"of niche items. This simulation study investigates selection bias in inflation estimation and compares correction methods across diverse data-generating processes. Through 40...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
