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Paper Citation Record · LEDGER

Carbon-Aware Computing for Datacenters

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.11750.

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

pith.paper-citation-record.v1
2106.11750 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:49:10.864421Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T03:26:35.707503Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5aeb5189-0df1-4673-a901-2bbdfa059bf8 · inbound

Achieving Dispatchability in Data Centers: Carbon and Cost-Aware Sizing of Energy Storage and Local Photovoltaic Generation cites this paper.

Achieving Dispatchability in Data Centers: Carbon and Cost-Aware Sizing of Energy Storage and Local Photovoltaic Generation Carbon-Aware Computing for Datacenters

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T12:49:10.864421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:49:10.864421Z digest=sha256:068465e066252f561b2c201b46f164c622303f0d4bbbee419eada115a8e349b0

Observation 2efe56a4-5d4c-474a-b9b8-f23a431f5ef9 · inbound

AI Infrastructure Sovereignty cites this paper.

AI Infrastructure Sovereignty Carbon-Aware Computing for Datacenters

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:07:12.033385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T03:02:37.251469Z digest=sha256:eb4d487b47f23ac3f20f0e53139c4aa9aa1cf329a3d3b685f2c5e06f7c21392b

Observation e5d4a2c4-59b1-414d-add5-b90918a75782 · inbound

CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms cites this paper.

CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms Carbon-Aware Computing for Datacenters

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-25T03:26:35.711242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-25T03:24:53.387430Z digest=sha256:d41ce8402901538959647e5173ca0c8a80abfab6e231071a4aa3c38fec629ba4

Observation 2c84b5c9-3cb9-4bf8-9243-c01c43272f57 · inbound

CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms cites this paper.

CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms Carbon-Aware Computing for Datacenters

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-02T13:26:25.969079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:26:25.969079Z digest=sha256:643137af19669c13b170aa0b3d4c4573a7aac62db2aa31947951f2ea6502be02

Observation af9c1b70-6a37-48c2-b9fa-a906f0694cf1 · inbound

Emission-Forecasting-Based Spatial-Temporal Carbon Response: A Multi-Agent Attention-Enhanced Deep Learning Framework cites this paper.

Emission-Forecasting-Based Spatial-Temporal Carbon Response: A Multi-Agent Attention-Enhanced Deep Learning Framework Carbon-Aware Computing for Datacenters

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T13:26:13.261866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:26:13.261866Z digest=sha256:53da0cf3e7e25ac3f0e191d9242f64bb8b89bb571c82ef6075fa571b1ac9d714