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  3. MobileKernelBench: Can LLMs Write Efficient Kernels for Mobi
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MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?

Stale17d ago
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Viability
0.0/10

Compared to this week’s papers

Stale evidence

Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: stale

Source paper: MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?

PDF: https://arxiv.org/pdf/2603.11935v1

Source count: 0

Coverage: 33%

Last proof check: 2026-03-19T18:48:05.835Z

Paper Conversation

Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.

Paper Mode

MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?

Overall score: 7/10
Lineage: a876c14d1227…
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Canonical Paper Receipt

Last verification: 2026-03-19T18:48:05.835Z

Freshness: stale

Proof: unverified

Repo: missing

References: 0

Sources: 0

Coverage: 33%

Missingness
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  • - references
  • - distribution_readiness_scores
  • - paper_extraction_scorecards
Unknowns
  • - distribution readiness has not been computed yet

Mode Notes

  • Corpus mode searches the research corpus broadly.
  • Paper mode pins trust state to the canonical paper kernel.
  • Workspace mode blends saved sources, prior evidence queries, and linked papers.

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Dimensions overall score 7.0

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Keep exploring

Builds On This
MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale
Score 4.0down
Builds On This
ProactiveMobile: A Comprehensive Benchmark for Boosting Proactive Intelligence on Mobile Devices
Score 4.0down
Builds On This
RooflineBench: A Benchmarking Framework for On-Device LLMs via Roofline Analysis
Score 5.0down
Prior Work
MobileDev-Bench: A Comprehensive Benchmark for Evaluating Language Models on Mobile Application Development
Score 7.0stable
Prior Work
KernelFoundry: Hardware-aware evolutionary GPU kernel optimization
Score 7.0stable
Prior Work
KernelBlaster: Continual Cross-Task CUDA Optimization via Memory-Augmented In-Context Reinforcement Learning
Score 7.0stable
Higher Viability
Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts
Score 8.0up
Higher Viability
Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization
Score 8.0up

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