arXiv AI
6d ago
RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks
arXiv:2608. 12004v1 Announce Type: cross Abstract: In modern AI frameworks, GPU kernels are key to overall system performance.
Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization
arXiv:2607. 23089v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface signals such as compilation feedback and profiling metrics.
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REFORGE: A Method for Benchmarking LLMs' Reverse Engineering Capabilities in Decompiled Binary Function Naming
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Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?
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KernelGenBench: A Multi-Source and Multi-Chip Benchmark for LLM-based Kernel Generation
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Agentic Harness for Real-World Compilers
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CodegenBench: Can LLMs Write Efficient Code Across Architectures?
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Protean Compiler: An Agile Framework to Drive Fine-grain Phase Ordering
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