Paper Citation Record · LEDGER

Mercury: A Code Efficiency Benchmark for Code Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.07844.

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

pith.paper-citation-record.v1
2402.07844 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:09:33.758152Z

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 a953c568-b32a-48a2-8830-da3a4598a9d6 · inbound

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models cites this paper.

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:33:14.974517Z

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.

Observation 12179005-66ad-4c07-82e8-74ae8c614eb2 · 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 Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:09:33.758152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4979600a-686b-490d-8971-c132fc019f26 · inbound

SimdBench: Benchmarking Large Language Models for SIMD-Intrinsic Code Generation cites this paper.

SimdBench: Benchmarking Large Language Models for SIMD-Intrinsic Code Generation Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:43:36.505732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d6aaf3f-2819-4815-bc29-b6e02d53aab1 · inbound

Benchmarking LLMs for Unit Test Generation from Real-World Functions cites this paper.

Benchmarking LLMs for Unit Test Generation from Real-World Functions Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T10:15:37.196364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6d0bf55-b295-46c0-97c6-dcc321a4be00 · inbound

PerfCoder: Large Language Models for Interpretable Code Performance Optimization cites this paper.

PerfCoder: Large Language Models for Interpretable Code Performance Optimization Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T22:43:38.162964Z

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.

Observation 7d81b9ba-92f2-4f54-8d98-7d5f10379b75 · inbound

InCoder-32B-Thinking: Industrial Code World Model for Thinking cites this paper.

InCoder-32B-Thinking: Industrial Code World Model for Thinking Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T18:58:08.657749Z

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.

Observation 94712a21-2629-4f2a-8dd1-9692b8afa02b · 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 Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:21:11.051841Z

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.

Observation 16dd232a-ff0a-4343-b6f4-aaccb9aeff26 · inbound

SWE-InfraBench: Evaluating Language Models on Cloud Infrastructure Code cites this paper.

SWE-InfraBench: Evaluating Language Models on Cloud Infrastructure Code Mercury: A Code Efficiency Benchmark for Code Large Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T09:56:51.755571Z

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.