Author

Vishakha Ramani

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#artificial intelligence Preprint Oct 2026

ROAR: Unifying Runs across Heterogeneous AI-Driven Research Systems

Each run of an AI-driven research system (ADRS) is an expensive search over a vast solution space, and dependable evaluation requires many runs, making run data both costly to produce and valuable to retain for large-scale analysis. Yet this data remains fragmented: teams operate in isolation, ADRS frameworks emit resu...

Leo Y. Lin, Vishakha Ramani, Z. B. Celik et al. · 0 citations

Preprint Sep 2026

An Approximate Queueing Model of LLM Inference Serving for SLO-Driven Autoscaling

Performance models of LLM servers support both latency evaluation and the design of controllers for autoscaling against service level objectives (SLOs) and for inference optimization. We model the multiplexed execution of prefill and decode operations with a tractable, approximate queueing model under Markovian assumpt...

Vishakha Ramani, Asser N. Tantawi · 0 citations