Paper Citation Record · LEDGER

Routing LLM Inference to the Cleanest Grid in Real Time

As of 8 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2608.06188.

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

pith.paper-citation-record.v1
2608.06188 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:00:31.923370Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact6
verified fuzzy7
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47448fd7-2e8b-49dc-a41a-a3291721df11 · outbound

This paper cites Marginal Emissions Factors for the U.S. Electricity System.

Routing LLM Inference to the Cleanest Grid in Real Time Marginal Emissions Factors for the U.S. Electricity System

Reference 1

Resolution: verified exact; doi, observed 2026-08-07T13:00:33.426997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1455f23e-b40d-4eda-b93d-0221111d4ee0 · outbound

This paper cites Marginal Operating Emissions Rate (MOER): methodology and validation.

Routing LLM Inference to the Cleanest Grid in Real Time Marginal Operating Emissions Rate (MOER): methodology and validation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:36.039428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e7bc1a16-3dda-438c-bfbb-1c271882c5e5 · outbound

This paper cites An Introduction to the Bootstrap.

Routing LLM Inference to the Cleanest Grid in Real Time An Introduction to the Bootstrap

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:35.789109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae05443b-d64e-4ea9-a6e3-975851def28e · outbound

This paper cites Carbon-Aware Computing for Datacenters.

Routing LLM Inference to the Cleanest Grid in Real Time Carbon-Aware Computing for Datacenters

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.193102Z

Source-reported events for the cited work

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Observation fffdd508-c9fa-485a-88b1-fb33357372b7 · outbound

This paper cites Let’ s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud.

Routing LLM Inference to the Cleanest Grid in Real Time Let’ s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.305345Z

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Observation e82bac1f-378a-4cf8-bdb2-2985f87b497d · outbound

This paper cites Chasing Carbon: The Elusive Environmental Footprint of Computing.

Routing LLM Inference to the Cleanest Grid in Real Time Chasing Carbon: The Elusive Environmental Footprint of Computing

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.468536Z

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Observation 7ae5d640-01ff-46da-af9d-1ca92e4fd04e · outbound

This paper cites Ecovisor: A Virtual Energy System for Carbon-Efficient Applications.

Routing LLM Inference to the Cleanest Grid in Real Time Ecovisor: A Virtual Energy System for Carbon-Efficient Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.582641Z

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Observation c90662ff-b400-457c-9fe5-dcf41e3a837c · outbound

This paper cites CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency.

Routing LLM Inference to the Cleanest Grid in Real Time CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.681481Z

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Observation 39bf7065-21dc-4ee0-97d6-e9ea9fc99b2b · outbound

This paper cites Greening Geographical Load Balancing.

Routing LLM Inference to the Cleanest Grid in Real Time Greening Geographical Load Balancing

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T13:00:34.011615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2ac576d9-9d38-478a-be79-073ac1e8aa63 · outbound

This paper cites Real-Time Carbon Accounting Method for the European Electricity Markets.

Routing LLM Inference to the Cleanest Grid in Real Time Real-Time Carbon Accounting Method for the European Electricity Markets

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.838041Z

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Observation 63255441-7677-48d0-8005-a96fe3940d50 · outbound

This paper cites Power Hungry Processing: Watts Driving the Cost of AI Deployment?.

Routing LLM Inference to the Cleanest Grid in Real Time Power Hungry Processing: Watts Driving the Cost of AI Deployment?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.921396Z

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Observation e03550cb-6947-442a-8e01-021fd2261017 · outbound

This paper cites Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service.

Routing LLM Inference to the Cleanest Grid in Real Time Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.999001Z

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Observation ba88a26e-6969-4f5f-b3e4-98aae1bed28a · outbound

This paper cites Sprout: Green Generative AI with Carbon-Efficient LLM Inference.

Routing LLM Inference to the Cleanest Grid in Real Time Sprout: Green Generative AI with Carbon-Efficient LLM Inference

Reference 14

Resolution: verified exact; doi, observed 2026-08-07T13:00:33.183484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d3fa7796-cfc8-47ce-9837-7dde5963efa4 · outbound

This paper cites DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency.

Routing LLM Inference to the Cleanest Grid in Real Time DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

Reference 15

Resolution: verified exact; doi, observed 2026-08-07T13:00:32.984354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 69785945-e45f-46f1-aa25-0a6aafd38773 · outbound

This paper cites Towards Environmentally Equitable AI via Geographical Load Balancing.

Routing LLM Inference to the Cleanest Grid in Real Time Towards Environmentally Equitable AI via Geographical Load Balancing

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.318532Z

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Observation 1a303a26-20db-44d3-a460-9ee8d61c5bee · outbound

This paper cites Energy and Policy Considerations for Deep Learning in NLP.

Routing LLM Inference to the Cleanest Grid in Real Time Energy and Policy Considerations for Deep Learning in NLP

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.407480Z

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Observation 732dad1d-95e2-4600-bbf0-62194ce8a950 · outbound

This paper cites Measuring the Carbon Intensity of AI in Cloud Instances.

Routing LLM Inference to the Cleanest Grid in Real Time Measuring the Carbon Intensity of AI in Cloud Instances

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.488926Z

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Observation a9b505ca-63f0-44c3-bb9f-ebe2f343ea95 · outbound

This paper cites Estimating Marginal CO2 Emissions Rates for National Electricity Systems.

Routing LLM Inference to the Cleanest Grid in Real Time Estimating Marginal CO2 Emissions Rates for National Electricity Systems

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.590547Z

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Unavailable: canonical work link unavailable.

Observation 11e2b943-2064-4579-8160-5e08f3ad9e45 · outbound

This paper cites Carbon Emissions and Large Neural Network Training.

Routing LLM Inference to the Cleanest Grid in Real Time Carbon Emissions and Large Neural Network Training

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.630891Z

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Observation 5646786f-c0a6-4687-a2ff-6597f600aa71 · outbound

This paper cites TowardstheSystematic Reporting of the Energy and Carbon Footprints of Machine Learning.

Routing LLM Inference to the Cleanest Grid in Real Time TowardstheSystematic Reporting of the Energy and Carbon Footprints of Machine Learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:35.580513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 43a98908-a110-409e-81be-d3c40d812166 · outbound

This paper cites Solyx AI Grid: Hardware-Telemetry-Aware Routing Across Geographically Distributed GPU Clusters.

Routing LLM Inference to the Cleanest Grid in Real Time Solyx AI Grid: Hardware-Telemetry-Aware Routing Across Geographically Distributed GPU Clusters

Reference 22

Resolution: verified exact; doi, observed 2026-08-07T13:00:32.686524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c58e9d3b-f534-4daf-afa9-1372a189abb5 · outbound

This paper cites EcoServe: Designing Carbon-Aware AI Inference Systems.

Routing LLM Inference to the Cleanest Grid in Real Time EcoServe: Designing Carbon-Aware AI Inference Systems

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.958563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13b15205-ebc9-44fe-a7c7-7cfa0a8827bf · outbound

This paper cites Serving Models, Fast and Slow: Optimizing Heterogeneous LLM Inferencing Workloads at Scale (SAGESERVE).

Routing LLM Inference to the Cleanest Grid in Real Time Serving Models, Fast and Slow: Optimizing Heterogeneous LLM Inferencing Workloads at Scale (SAGESERVE)

Reference 24

Resolution: verified exact; doi, observed 2026-08-07T13:00:32.454291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f3e6692b-2605-4406-9297-f2d904efb5c2 · outbound

This paper cites GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization.

Routing LLM Inference to the Cleanest Grid in Real Time GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:32.162092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ca612e8b-fdd6-422c-8092-ca6911bde83d · outbound

This paper cites v3 API documentation.

Routing LLM Inference to the Cleanest Grid in Real Time v3 API documentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:35.324632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 06e93b2c-f960-4d59-baa6-e2e09638481c · outbound

This paper cites North-America MOER model version 2026-03-01 release notes (expanded renewable- curtailment detection; zero-MOER values during modeled curtailment).

Routing LLM Inference to the Cleanest Grid in Real Time North-America MOER model version 2026-03-01 release notes (expanded renewable- curtailment detection; zero-MOER values during modeled curtailment)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:35.113190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3384a559-c0ff-4e10-8389-edf7e8ecd3ea · outbound

This paper cites The GHG Protocol for Project Accounting.

Routing LLM Inference to the Cleanest Grid in Real Time The GHG Protocol for Project Accounting

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:34.922297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b291e807-2dd8-4536-9923-94fc48250d60 · outbound

This paper cites Guidelines for Quantifying GHG Reductions from Grid-Connected Electricity Projects.

Routing LLM Inference to the Cleanest Grid in Real Time Guidelines for Quantifying GHG Reductions from Grid-Connected Electricity Projects

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:34.716609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 60a57892-9a93-4d95-967d-9c5d5f564666 · outbound

This paper cites an unresolved cited work.

Routing LLM Inference to the Cleanest Grid in Real Time Unresolved cited work

Reference 2007

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:00:34.514625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c19ea45-c4fc-442c-a38d-19d9aca21f10 · outbound

This paper cites Carbon Emissions and Large Neural Network Training.

Routing LLM Inference to the Cleanest Grid in Real Time Carbon Emissions and Large Neural Network Training

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.717634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb7ba158-1ba9-450c-8a7b-44929659aa1d · outbound

This paper cites EcoServe: Designing Carbon-Aware AI Inference Systems.

Routing LLM Inference to the Cleanest Grid in Real Time EcoServe: Designing Carbon-Aware AI Inference Systems

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:31.049555Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.