Abstract: Modern compilers, such as LLVM, are complex. Due to their complexity, manual testing is unlikely to suffice, yet formal verification is difficult to scale. End-to-end fuzzing can be used, ...
Abstract: Large language models (LLMs) play a crucial role in intelligent code generation tasks. Most existing work focuses on pretraining or fine-tuning specialized code LLMs, e.g., CodeLlama.
MLX support on Apple Silicon is in progress. We will make necessary updates to the repository once it is available. However, the generation pattern and post-training strategies of dLLMs remain ...
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