🏗️ Building on HF

Dipankar Sarkar PRO

dipankarsarkar

https://www.dipankar.cc

AI & ML interests

Building the AI-native stack. Agents as infrastructure, safety as architecture, performance as plumbing. I publish the receipts: papers, datasets, demos.

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authored a paper about 8 hours ago

The Correctness Illusion in LLM-Generated GPU Kernels

authored a paper about 8 hours ago

Before the Pull Request: Mining Multi-Agent Coordination

authored a paper about 8 hours ago

Epistral Network: Revolutionizing Media Curation and Consumption through Decentralization

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LLM-generated GPU kernels pass the standard correctness test and are still wrong.

The industry oracle is one line: torch.allclose at one shape, one dtype, one seed. Every modern kernel benchmark uses it. It is blind to whole bug classes.

So I built the receipts:
- a 26-op corpus of correct and LLM-buggy kernels
- a differential fuzz vs an fp64 reference that catches what allclose misses
- a live demo you can click

The Correctness Illusion in LLM-Generated GPU Kernels (2606.20128)
dipankarsarkar/gpuemu-corpus
dipankarsarkar/the-correctness-illusion

What is your teams actual correctness oracle for generated kernels?