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Paper Citation Record · LEDGER

Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2407.04014.

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

pith.paper-citation-record.v1
2407.04014 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:59:18.417892Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T05:27:05.508048Z

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 5746f32f-31dc-40ec-b425-a3aa15be497f · inbound

Engineering AI Judge Systems cites this paper.

Engineering AI Judge Systems Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-12T11:59:18.417892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:59:18.417892Z digest=sha256:e31abc4debc9a210ba31d1d680b6721182f13303a7e1bebcecbf5f3ae22934df

Observation 02a7ef6e-46bd-4a94-8d3d-676a8578f343 · inbound

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG cites this paper.

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T20:34:34.718781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:34:34.718781Z digest=sha256:c155aa043d458fbc65c31b11e956692b6cc2df80de6852b3416679818f38eb89

Observation c07eab1b-1cbf-4902-99da-4d8c2171de48 · inbound

Green-LLM: Optimal Workload Allocation for Environmentally-Aware Distributed Inference cites this paper.

Green-LLM: Optimal Workload Allocation for Environmentally-Aware Distributed Inference Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:27:05.511017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T05:25:27.501548Z digest=sha256:11fbb840dda0de13616f91ed52aaecc86788baf8e0170ef4d5dc80bb580babd8

Observation 7890c92f-782f-4a20-ba26-b54ca78b9d55 · inbound

SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference cites this paper.

SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:07:29.562035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-16T07:05:56.380048Z digest=sha256:0beffa566de82d565826705ab5e3370ee676a8ca43001448b0d3c5574a89850f

Observation 31dd7364-56c3-4974-a42f-ed9b15fb2ed5 · inbound

The Energy Cost of Execution-Idle in GPU Clusters cites this paper.

The Energy Cost of Execution-Idle in GPU Clusters Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:30:51.549870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T19:04:25.951890Z digest=sha256:75a1b26bc1c6287600976bd5fec47bc84942a834b127af014502d4775e186b58

Observation 4853a9d3-d336-4dee-9693-38352c8ec985 · inbound

Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds cites this paper.

Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:40:57.705651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T18:01:05.284509Z digest=sha256:6c4d11fdf2d57a3f76e1884b497db865eb1463ea97879c228e9e69c63412c4ab

Observation adce9cb2-c3c7-48e6-b56e-dfd787e32ea2 · inbound

Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds cites this paper.

Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-13T08:29:35.019973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T08:29:35.019973Z digest=sha256:59a09b59bd9d16be79dc20951ebecb8647851f52248714a7dcd4ea5b04f52e7e