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Rebuilding vanity address generator for TON from scratch with AI, achieving up to 286,000x speedup through a series of domain-specific optimizations.
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Predictions and thoughts on AI progress in 2026.
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Lessons learned from scaling documentation-driven black-box fuzzing pipelines to billions of tokens, practical deduplication strategies, discovered scaling laws, and initial explorations into white-box fuzzing for future expansion.
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A fresh and simple black-box approach to fuzzing compilers using large language models to generate test cases from documentation and specification.
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A detailed benchmarking study exploring entropy and randomness across 52 large language models using diverse prompting strategies, revealing notable biases and significant variability influenced by model architectures and prompt engineering.