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Paper Citation Record · LEDGER

Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.17215.

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

pith.paper-citation-record.v1
2406.17215 v3

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 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:14:51.347955Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:16:11.846764Z

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 5fdddbc2-1888-4cde-a77b-7c516bf7d35f · inbound

Enhancing LLMs for Power System Simulations: A Feedback-driven Multi-agent Framework cites this paper.

Enhancing LLMs for Power System Simulations: A Feedback-driven Multi-agent Framework Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T15:14:51.347955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:14:51.347955Z digest=sha256:76f334ed21cde8c3a8178b061bfd460ed2569721535ab0e36f799d4b13beab4c

Observation 49fbeea1-1746-4b26-9dd1-fef31da96d52 · inbound

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks cites this paper.

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T04:32:57.817116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:32:57.817116Z digest=sha256:5e62186913df86e3c62da366f30eff2fed0973f33ec3671a5c97d96a6ffbce81

Observation 5fb1a216-7aa3-4cb0-82ac-34af12674da0 · inbound

Large Language Model Interface for Home Energy Management Systems cites this paper.

Large Language Model Interface for Home Energy Management Systems Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:45.489162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:45.489162Z digest=sha256:5335fae7f433e229a9371ddbe8da1571a678fc74a6eb5e741babc6db5d1ab1b5

Observation dffafe1c-879e-48a4-89b8-0734e00bc412 · inbound

PFAgent: A Tractable and Self-Evolving Power-Flow Agent for Interactive Grid Analysis cites this paper.

PFAgent: A Tractable and Self-Evolving Power-Flow Agent for Interactive Grid Analysis Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:56:04.839518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T15:15:47.810263Z digest=sha256:81f59dab5a1cb6cfe8100ecfb263cc8bb5620b8f5447206468033ac76b13e9d4

Observation a929995b-439d-4d4c-a6d1-da9f9f6724c0 · inbound

Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation cites this paper.

Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-01T20:16:11.848394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T21:25:51.439330Z digest=sha256:c06dcd68d291f96375964cc3c421cecfedf73aaf8cbf1f9710c6c456f5984c70