Pith. sign in

Paper Citation Record · LEDGER

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers

As of 24 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.17514.

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

pith.paper-citation-record.v1
2607.17514 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:48:46.787725Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 88725e7f-5a1b-4c19-b016-7f9704c61fb3 · outbound

This paper cites Recalibrating global data center energy-use estimates,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Recalibrating global data center energy-use estimates,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:44.530907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:44.530907Z digest=sha256:bcce138d9ce5e5939ad4495fd92e95755ef87e234849e838cbdedfd1fb699824

Observation f9b437b7-88c6-476a-ba43-877247746beb · outbound

This paper cites Energy and policy con- siderations for deep learning in nlp,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Energy and policy con- siderations for deep learning in nlp,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:44.634785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:44.634785Z digest=sha256:b830849a5ac6ca1cafb325c018b4985f3eaab3cab1d8d7702e761f938ff30d7f

Observation 621da9c6-d820-4805-bac4-850795f55322 · outbound

This paper cites Data center power system stability—part i: Power supply impedance modeling,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Data center power system stability—part i: Power supply impedance modeling,

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:44.775009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:44.775009Z digest=sha256:424e068f42c686295a2fa06df035a37c8cb56966c641aed048f3a8099e9b8a07

Observation 744c026d-866b-4aef-b7bd-5a4fcbdc6da2 · outbound

This paper cites Risk-aware energy scheduling for edge computing with microgrid: A multi-agent deep reinforcement learning approach,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Risk-aware energy scheduling for edge computing with microgrid: A multi-agent deep reinforcement learning approach,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:44.903888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:44.903888Z digest=sha256:7ff3af4e4c4b8d104baf7db130827afda0bf66ae8a1bf3e81b877beb29046b4b

Observation 091b3147-17dd-470f-9f71-722934601d88 · outbound

This paper cites Electricity demand and grid impacts of ai data centers: Challenges and prospects,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Electricity demand and grid impacts of ai data centers: Challenges and prospects,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.060061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.060061Z digest=sha256:5eca64b51583f8cebc19d09a04cdec6e58ac8dbffec58b53a5f470272b041e2f

Observation 5b7c3303-0339-49d8-8fad-dcf24b405c5a · outbound

This paper cites Toward optimal operation of internet data center microgrid,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Toward optimal operation of internet data center microgrid,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.326720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.326720Z digest=sha256:ff687581d51ebc28b7d1cc8e826b14c390d0cc13b31063f3986682895367fafd

Observation 403df49b-520e-4ab1-bb50-55bc7349b4a8 · outbound

This paper cites Safari, K.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Safari, K

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.478754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.478754Z digest=sha256:eced3ec955616c17a48027976f93030a93da6fe63fdfacb21874ce6bcc198a3d

Observation 1245e816-bd3a-401c-8e4e-2f9dc7ddf5b4 · outbound

This paper cites Towards accurate prediction for high-dimensional and highly-variable cloud workloads with deep learning,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Towards accurate prediction for high-dimensional and highly-variable cloud workloads with deep learning,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.617898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.617898Z digest=sha256:ff8b8903f407a7d9330f10da3e3b5343b4efddbc337f51de484676e4e2981a22

Observation 0f6e4c39-a7b1-4ad6-8918-7915f7972527 · outbound

This paper cites A review of machine learning-based photovoltaic output power forecasting: Nordic context,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers A review of machine learning-based photovoltaic output power forecasting: Nordic context,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.735995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.735995Z digest=sha256:c40de50e2d1408fddc7b0e6ffcafe2c05344d741695f84bfeab0bc4cb5e01459

Observation 21ecb73c-217f-4518-b45a-28fea7216e5b · outbound

This paper cites The cost of photovoltaic forecasting errors in microgrid control with peak pricing,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers The cost of photovoltaic forecasting errors in microgrid control with peak pricing,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.805713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.805713Z digest=sha256:00b6cb523171450dd3867382f6f0977db4f7d4ea75bdff3e7ce2315f5de35f37

Observation c00ca735-079d-4437-8349-687c966e350a · outbound

This paper cites Smart “predict, then optimize.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Smart “predict, then optimize

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.873344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.873344Z digest=sha256:21e830f7fb45591be727ff96e45d8ef3785d027ae5ee11cd78f915b403d13aa1

Observation 8b3598bd-93e0-4df3-8392-0cd26045ec55 · outbound

This paper cites Task-based end-to-end model learning in stochastic optimization,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Task-based end-to-end model learning in stochastic optimization,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.970074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.970074Z digest=sha256:42ae58fa59d084693502ebd810df8f670fb90af9b9a0648453fc90a371be50b7

Observation 1c5e3461-2ab3-4a7e-b62c-794bed093ce2 · outbound

This paper cites Decision-Focused Learning for Power System Decision-Making Under Uncertainty,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Decision-Focused Learning for Power System Decision-Making Under Uncertainty,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:46.072801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:46.072801Z digest=sha256:01f0513e4854189805ff222ca84952a9c67bb246bace0deb65b178ad089daf0e

Observation 4b9ab54d-26c1-44de-8149-72f7f208a027 · outbound

This paper cites Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:46.237130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:46.237130Z digest=sha256:b5cd232266a3408b62f61cd87d47c0cf66975bb75161e23da6c5ced4baa3d73b

Observation 1e4dfddb-cb1a-4c96-8c05-9cd596a40a8d · outbound

This paper cites Branch flow model: Relaxations and convexification—part i,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Branch flow model: Relaxations and convexification—part i,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:46.430057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:46.430057Z digest=sha256:ba34190ec9a2b5970da464c24ab294a6a4889e0fbaeab56a4aff4eed6940af80

Observation cd4bf4ee-2243-4920-b1b6-0601002aa684 · outbound

This paper cites Optnet: Differentiable optimization as a layer in neural networks,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Optnet: Differentiable optimization as a layer in neural networks,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:46.623055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:46.623055Z digest=sha256:d02bc5b776fff0cad39d092563767fb63e387a793db1ab93b994c2e5b884af3f

Observation 46116c3b-4001-4fbe-9193-cb70f040eb84 · outbound

This paper cites Differentiable convex optimization layers,.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Differentiable convex optimization layers,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:46.787725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:46.787725Z digest=sha256:cd27d1fe4d3e46fadcf4a6fb180a38bf0d3a9ed32ffb9c7f364c33dfaaaaeea1

Observation fb8f4686-4188-41cc-b252-9f3403c79501 · outbound

This paper cites Electricity Demand and Grid Impacts of AI Data Centers: Challenges and Prospects.

A Predict-then-Schedule framework for Power Distribution Networks with AI Data Centers Electricity Demand and Grid Impacts of AI Data Centers: Challenges and Prospects

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T17:48:45.178671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:48:45.178671Z digest=sha256:c1b31957073e2db8a50fbe356047f91b637e390f95130d0f6389a9a1eae96ef9

Pith citing papers

No inbound Pith citation observations are available.