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A big advantage of stepwise refinement is that when you want to explore a protocol variant, you don't start from scratch. You go back up to the appropriate level of abstraction, change one refinement step, and get a different protocol that still satisfies the same high-level specification. This is systematic design space exploration. With LeaseGuard, for example, we started modeling a lease protocol for Raft early. While refining the abstract spec, we discovered two optimizations we hadn't anticipated, including inherited lease reads, which we probably wouldn't have found without thinking at multiple levels of abstraction.
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Key strengths include strong proficiency in Indian languages, particularly accurate handling of numerical information within those languages, and reliable execution of tool calls during multilingual interactions. Latency gains come from a combination of fewer active parameters than comparable models, targeted inference optimizations, and reduced tokenizer overhead.
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Methodological rationale. The evaluation adopts an adversarial case-study methodology. In safety analysis, demonstrating robustness typically requires extensive positive evidence. By contrast, demonstrating vulnerability requires only a single concrete counterexample. Our goal was not to statistically estimate failure rates, but to establish the existence of critical vulnerabilities under realistic interaction conditions.
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