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A Translational Note on AI Safety Evaluation
Madhava Gaikwad
Recent studies report that automated red-teaming finds more vulnerabilities, at lower cost, than human red-teaming on standard AI safety benchmarks, and some read this as evidence…
The Abstention Protocol: RCA for Clos Fabrics
Madhava Gaikwad, Deepak Pandey
Root cause analysis (RCA) in large datacenter networks is challenging because telemetry is noisy, partial, and asynchronous. Score-based approaches degrade under these conditions,…
Did You Check the Right Pocket? Cost-Sensitive Store Routing for Memory-Augmented Agents
Madhava Gaikwad
Memory-augmented agents maintain multiple specialized stores, yet most systems retrieve from all stores for every query, increasing cost and introducing irrelevant context. We form…
Murphys Laws of AI Alignment: Why the Gap Always Wins
Madhava Gaikwad
We study reinforcement learning from human feedback under misspecification. Sometimes human feedback is systematically wrong on certain types of inputs, like a broken compass that…
NPO: Learning Alignment and Meta-Alignment through Structured Human Feedback
Madhava Gaikwad, Ashwini Ramchandra Doke
We present NPO, an alignment-aware learning framework that operationalizes feedback-driven adaptation in human-in-the-loop decision systems. Unlike prior approaches that treat alig…