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cs.AI2026
RippleCP: Measuring Counterfactual Checkpoint Advantage in Coding Agents
Mayur Akewar, Ravi Ranjan
Agent checkpoint systems decide what state is recovery-relevant, how to snapshot it, and whether rollback is admissible. None decides which of the safe boundaries they expose are w…
cs.AI2026
SafeCommit: Certifying When Memory-Grounded Agents May Safely Act
Mayur Akewar, Ravi Ranjan
Long-horizon agents increasingly use persistent memory and tools to take actions with external side effects. A central failure mode is premature commitment: an agent acts before re…
cs.AI2026
PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs
Ravi Ranjan, Utkarsh Grover, Xiaomin Lin +1
Large language models (LLMs) can provide automated feedback in educational settings, but aligning an LLMs style with a specific instructors tone while maintaining diagnostic correc…