Author

Arjun Subramanian

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Preprint Oct 2026

Asymmetric Repository Lineage Modeling and Verifier-Guided Coordination in Concurrent AI Coding Agents

Concurrent AI coding agents create a coordination problem in which cheap signals may prioritize work, but only an executable checker can establish the property being claimed. We study this separation through a property-scoped verification contract and MERGEGYM, a three-track benchmark for open-time scope forecasting, r...

Arjun Subramanian, George Xu, N. Karthik · 0 citations

#machine learning Preprint Oct 2026

Repeated-Measure Leakage, Distribution Shift, and Reliability under Partial Observation in Patient World Models

Patient world models are increasingly proposed for longitudinal prediction, intervention-aware reasoning, and clinical-trial simulation. Causal or clinical intervention validity is distinct from predictive generalization and reliability; before making stronger claims, the underlying predictive state should generalize a...

Arjun Subramanian · 0 citations

Jul 2026

AI Agent Pull Requests on GitHub: Frequency, Structure, and Merge Conflict Rates

The AIDev-pop dataset is used to provide the first empirical examination of the prevalence of concurrent submission using PRs authored by agents, and a classification system based on the detection of conflict reported by git is developed.

George Xu, Arjun Subramanian, N. Karthik · arXiv.org · 0 citations