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Paper Citation Record · LEDGER

Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.13192.

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

pith.paper-citation-record.v1
2309.13192 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:40:48.222766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T20:25:05.449148Z

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 44a45fd4-3775-427b-b034-63a4e7df057a · inbound

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights cites this paper.

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-22T20:25:05.450924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T20:24:01.224251Z digest=sha256:62b290855f848d9bfbb1cbd84a67361f5d0f2b744e380c62de2e8a53f3e81591

Observation 51bf3c3f-cc27-48d7-b3a4-88c760666f41 · inbound

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

Electricity Demand and Grid Impacts of AI Data Centers: Challenges and Prospects Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-04T22:40:48.222766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:40:48.222766Z digest=sha256:915efc1da3759faba6a911a0de88c8ec8e95eebe1d8bcb83b8a096a92f3fb6df