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The State Key Laboratory of Blockchain and Data Security, Zhejiang University
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Achieving up to 3.14x speedup in pointer analysis by leveraging compiler optimizations could revolutionize static analysis performance benchmarks.
A new optimization-based approach to inductive invariant synthesis achieves an 86% increase in benchmark solvability compared to traditional methods.
Persona conditioning in LLMs can be exploited to amplify inference costs by over 200 times, revealing a critical vulnerability in their deployment.
LLMs can supercharge traditional compilers, achieving up to 6.88x speedups by synthesizing precise compiler hints that unlock hidden optimization opportunities.
