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#Code Generation
Four entries on this site carry the Code Generation tag: three papers and one post, dated 2026. Explore the full list of related work below.
Papers
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Test-Input Generation for Tensor Programs: What Actually Finds Kernel Bugs
Paper · 2026 · arXiv · cited by 0 Seven test-input generation strategies evaluated on the 26-op gpuemu corpus, reporting bug recall and control false-positive rate. -
The Correctness Illusion in LLM-Generated GPU Kernels
Paper · 2026 · arXiv · cited by 6 Fixed-shape allclose checks used by LLM-kernel benchmarks certify buggy kernels as correct. Under op-schema-aware seeded fuzzing with an fp64 reference and per-(op, dtype) tolerances, a 26-op corpus shows 10 of 10 seeded illusions caught and 16 of 16 controls. -
Before the Pull Request: Mining Multi-Agent Coordination
Paper · 2026 · arXiv · cited by 0 Studies how concurrent coding agents claim, divide and collide over shared work before a pull request exists, using grite, a git-native append-only coordination log. Duplicate work falls from 78% to 0% and failure modes become minable from the log.
Posts
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Why GPU Kernel Benchmarks Miss Real Bugs
Post · 2026 Passing a correctness benchmark and being correct in production are different claims for LLM-generated GPU kernels — the gap comes down to which inputs get sampled.