AI Research
Cross-Dialect Generalization Without Retraining: Benchmarks and Evaluation of Schema-Derived Constrained Decoding for MLIR
Multi-Level Intermediate Representation (MLIR) underlies modern ML compiler infrastructure (TensorFlow, JAX/StableHLO, PyTorch Inductor, IREE), yet appears only in trace amounts in code-LM pretraining corpora. MLIR is also extensible by design: new dialects ship per application d...
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ArXiv CS.AI
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ArXiv CS.AI
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This research introduces a novel method for LLMs to generate valid MLIR code across different dialects without requiring exhaustive retraining. This greatly improves efficiency and scalability for ML compiler development by leveraging syntactic rules from dialect specifications, a crucial step for deploying AI in complex software engineering tasks.
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