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Paper Citation Record · LEDGER

How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2406.06647.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2406.06647 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:49:14.651526Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7d2a4cf5-ea26-4afe-b485-b41552f8def0 · inbound

SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence cites this paper.

SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T23:49:14.651526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:49:14.651526Z digest=sha256:84d8b18e171f24296117ed4cfec264ead91169b73674049418f99c8d4747e8f8

Observation 30d9c9c0-b689-4a93-92d7-6778f68f5276 · inbound

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting cites this paper.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:56.978627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:34:56.978627Z digest=sha256:8c8b84944a83be6c6713ca9aeafdcbbed163bd3fdab36dd72336615e8316f37d

Observation d768de9e-9a5d-4dd6-91bd-2962dc171164 · inbound

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization cites this paper.

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T12:50:27.276056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:50:27.276056Z digest=sha256:c53396d8a3441efc4ac931fa48499ffa31a6f6e1a2706b3c28a8598525b673fc

Observation 2dec1611-4a8a-4c52-a7a3-d945316cc130 · inbound

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis cites this paper.

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:33.646855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:09:33.646855Z digest=sha256:5efd9c41a3c30ac6c5b3aa9d39ac0f8653caf690bcb17cef59eb21d40723bfe8

Observation cb0bb92f-2fc3-4a4d-8b01-d2da6116c80e · inbound

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming cites this paper.

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T22:13:43.518709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:13:43.518709Z digest=sha256:41d378fa8d6baae326bd6090ce4dd36d08b1f73cfce803605e73a0e5a948542a

Observation c293c707-cac1-4ec4-ae8e-dd7aaf8ce2fc · inbound

Do AI Models Dream of Faster Code? An Empirical Study on LLM-Proposed Performance Improvements in Real-World Software cites this paper.

Do AI Models Dream of Faster Code? An Empirical Study on LLM-Proposed Performance Improvements in Real-World Software How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-18T06:41:00.377223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T06:39:42.391102Z digest=sha256:9347e9dd4fb1d2ceeaa7bb06290acfa11410b417213e5ad6f3dd677a493726f1

Observation b79705da-b2ed-4a60-a7cc-a2ec2bb0b2fe · inbound

Incisor: Ex Ante Cloud Instance Selection for HPC Jobs cites this paper.

Incisor: Ex Ante Cloud Instance Selection for HPC Jobs How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-09T01:29:32.641798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T17:58:27.359369Z digest=sha256:0afee8476e2f3e1dfa732919a87bd358ed4021088490814965a173e7c1f7c747

Observation 6cdbc155-8baa-47d9-b227-9f2bf039c6cb · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 102

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:26:04.505509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T17:37:51.790000Z digest=sha256:0e19daf7a0461cb9adeb265c3cc4a1048d9364afd7e622d7985110913a628d14

Observation 7017ec4e-d55a-4353-abe7-e587c1287e11 · inbound

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves cites this paper.

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:57:04.734018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T01:52:50.908041Z digest=sha256:aab0a4c86e117725069dc88c9f7820fddf17325d7d599363dc3b4a6ddc0e0c38

Observation 8d852ec3-e499-4966-b42c-fe08046b9255 · inbound

CodegenBench: Can LLMs Write Efficient Code Across Architectures? cites this paper.

CodegenBench: Can LLMs Write Efficient Code Across Architectures? How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-02T00:06:23.728937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T13:38:48.308683Z digest=sha256:600024319ba36aebab68c67afd7c6a3ca82d45f472ef7489cb1f94e6d5e11feb

Observation fdfac164-c18f-47f9-8ef5-28ca3bffd16d · inbound

Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation cites this paper.

Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-02T18:57:17.211389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T21:43:14.839335Z digest=sha256:59cf7c267efd50e6702ac31c5e20ddb12a7337bb165216f508654f13d3b16559

Observation 3d4bf8c9-e6ec-4ee8-a30d-61e4370a78c6 · inbound

SkelDPO: A Skeleton-Guided Direct Preference Optimization Framework for Efficient Code Generation cites this paper.

SkelDPO: A Skeleton-Guided Direct Preference Optimization Framework for Efficient Code Generation How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:07:17.709938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T21:41:02.035059Z digest=sha256:c28d46c7dc8f41c55c39ff4952a3a35741628ec00ce6c1816ae9436aef65faf8

Observation 9afc1ee1-36a1-4e3d-8582-c4299f6b5583 · inbound

Correct but Slow: An Empirical Study of the GPU Kernel Evaluation Gap in Modern Domain-Specific Languages cites this paper.

Correct but Slow: An Empirical Study of the GPU Kernel Evaluation Gap in Modern Domain-Specific Languages How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 37

Resolution
unresolved
no resolver link, observed 2026-07-11T19:02:39.314928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T19:02:39.314928Z digest=sha256:2290253ffb8c06d5fa1add921e2d44aad1497b3158b9205abd1f6533209385f7

Observation 40d11d73-0714-4c4e-808d-fc7a50f7cc5f · inbound

PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization cites this paper.

PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T12:12:59.345502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:12:59.345502Z digest=sha256:e12da7e663f5acab0d10f2a1f51565958b9fb1aaf5267d2138d69768d33bf9b5

Observation 494ef898-6c9f-4e1c-a8d7-d80367638d85 · inbound

Reinforcement Learning for Code Optimization cites this paper.

Reinforcement Learning for Code Optimization How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T01:01:38.353080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:01:38.353080Z digest=sha256:76c26184aa1c110708ff40362d596abad88d3447b7d0e7afbcfad019859b743f