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Paper Citation Record · LEDGER

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies

As of 11 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2606.18789.

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

pith.paper-citation-record.v1
2606.18789 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T19:54:36.660981Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:19:18.585287Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dfd5e0a5-8c24-456e-a4e9-265b26f40713 · outbound

This paper cites Agentbench: Evaluating llms as agents,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Agentbench: Evaluating llms as agents,

Reference 1

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:79fdf94c649585f734b9470077f07e94d463b0237e16d15e9fb50006f3ada8ca

Observation a39d4bb2-6ff1-404f-84dc-500d82c0f89a · outbound

This paper cites SWE-bench: Can language models resolve real-world github issues?.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies SWE-bench: Can language models resolve real-world github issues?

Reference 2

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:883a62dd0ba8a3c74ff9a0bac1df864d5a3dbd765ed92aba650ac945bb4c0f15

Observation 2cef0810-b63d-436d-a9f9-f7e42cdb7f2b · outbound

This paper cites WebArena: A realistic web environment for building autonomous agents,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies WebArena: A realistic web environment for building autonomous agents,

Reference 3

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:6263b1d0f1a359644dd1a4263dcb67c13c8012e528611e6645cfdfcaf046f936

Observation 3ef0a45b-f77a-48ac-85be-b390021d2284 · outbound

This paper cites OSWorld: Benchmarking multimodal agents for open-ended tasks in real computer environments,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies OSWorld: Benchmarking multimodal agents for open-ended tasks in real computer environments,

Reference 4

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:2213c2c1916f03cdd961d0f9a1df58893e99b2ed105e7eefab543496e5ed30e4

Observation d58066b2-98e7-4c28-ae93-dcdf9f772d21 · outbound

This paper cites τ-bench: A benchmark for tool-agent-user interaction in real-world domains,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies τ-bench: A benchmark for tool-agent-user interaction in real-world domains,

Reference 5

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:b9ba47603c950ed733b2bc4aabfb00bedfde1ebf6e43b1460e94576a99214c9a

Observation a056173f-8885-4de9-a020-6740a3a65a46 · outbound

This paper cites MLAgentBench: Evalu- ating language agents on machine learning experimentation,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies MLAgentBench: Evalu- ating language agents on machine learning experimentation,

Reference 6

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:a0cfa553658490b8e1228d9da2d41a0ed9f93fd113597c5b4887dd31955a0413

Observation 0fcedf20-bf9e-418c-acf0-0d3be0aa1a2c · outbound

This paper cites PowerAgent: A road map toward agentic intel- ligence in power systems: Foundation model, model context protocol, and workflow,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies PowerAgent: A road map toward agentic intel- ligence in power systems: Foundation model, model context protocol, and workflow,

Reference 7

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:7e2e8b181a7920becc3591b0a66b8a0bd18cff5d3cd512cc4f9fb36484489b90

Observation a98ab837-bbc9-4ec1-bc7b-394427dab395 · outbound

This paper cites Exploring the capabilities and limitations of large language models in the electric energy sector,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Exploring the capabilities and limitations of large language models in the electric energy sector,

Reference 8

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:84190ddaa4663ea0208f8aa21a86157cd50997ad7fb9a96aa93ca3a2a0aa11c8

Observation 32fb1fc1-61da-43a3-bfd6-e569de20c411 · outbound

This paper cites X-gridagent: An llm-powered agentic ai system for assisting power grid analysis.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies X-gridagent: An llm-powered agentic ai system for assisting power grid analysis

Reference 9

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arxiv_id, observed 2026-07-04T02:19:22.617567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:bd3a056e78adb91cb073547a3cceb32058ae3b12b8c8def90c686307dd380b78

Observation 2e7b95f6-ff5f-4330-ac40-7bba105087b5 · outbound

This paper cites Grid copilot: A large language model (llm) based framework for transforming long-term planning analyses,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Grid copilot: A large language model (llm) based framework for transforming long-term planning analyses,

Reference 10

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:b0adf2e90e670eb03a33e3a3bdd97acce9bbb43c9b5cd9d8f63c9b58e833eba5

Observation 4fd9dd72-9843-485d-a1ec-cdb5c3ade8b3 · outbound

This paper cites The power grid library for benchmarking AC optimal power flow algorithms,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies The power grid library for benchmarking AC optimal power flow algorithms,

Reference 11

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:9af2622a719c7fe9b7bb549c2b41dfb12d6a3db51ee96c246c51d333854a0472

Observation f23f40c3-07ce-4bd7-8f65-b362f9c27071 · outbound

This paper cites Recent developments in security-constrained AC optimal power flow: Overview of challenge 1 in the ARPA-E grid optimization competition,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Recent developments in security-constrained AC optimal power flow: Overview of challenge 1 in the ARPA-E grid optimization competition,

Reference 12

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:b8bf1711589e339a0c5716a0b98e93913eda326d918c946d8eca605a7c26010f

Observation d07ddccf-a6a5-406b-b7aa-51fa07a11619 · outbound

This paper cites State-of-the- art, challenges, and future trends in security constrained optimal power flow,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies State-of-the- art, challenges, and future trends in security constrained optimal power flow,

Reference 13

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:72e7f420ac65c54a05fdd1eff45064b8b34b3e52fab580b7cf4b927c1662e457

Observation 7628128d-cb4a-40ed-879b-2761c3c82668 · outbound

This paper cites The N-K problem in power grids: New models, formulations and numerical experiments,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies The N-K problem in power grids: New models, formulations and numerical experiments,

Reference 14

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:02f7518f76b018e787b7737630e5d040b80093efb74003b1c1ae4b53167fee96

Observation c7bb87f0-2566-4a09-bd6f-94f37c1a5e39 · outbound

This paper cites Optimization strategies for the vulnerability analysis of the electric power grid,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Optimization strategies for the vulnerability analysis of the electric power grid,

Reference 15

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:c514eb18cecf2fd517e88239fb70c3f639f833efdb1220d4ae694363b5c723eb

Observation 2415d203-8803-4fa8-8512-30197ac8d0b1 · outbound

This paper cites Severe multiple contingency screening in electric power systems,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Severe multiple contingency screening in electric power systems,

Reference 16

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:3f5e64ec414da15793c0ddc90a5de193d424480b4540bf3db8bf91b0317ee01c

Observation a2d9c764-41f0-4d72-87c4-fe62dd7d575a · outbound

This paper cites Fast and reliable screening of N-2 contingencies,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Fast and reliable screening of N-2 contingencies,

Reference 17

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:f83ed769f5206b17528b7048542281d772ff94ceb296e27cc09e15646d47c43f

Observation 45dbb139-bd5d-4b01-9a8a-6a5aa967dc58 · outbound

This paper cites DeepOPF: A deep neural network approach for security-constrained DC optimal power flow,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies DeepOPF: A deep neural network approach for security-constrained DC optimal power flow,

Reference 18

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:01633b5470d1bcdc44cb32bdcf6bdb9d01c705e54f370d193427f40a54b05a48

Observation 226997e0-663b-44aa-b8bb-8124b6117bad · outbound

This paper cites CANOS: A fast and scalable neural AC-OPF solver robust to N-1 perturbations,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies CANOS: A fast and scalable neural AC-OPF solver robust to N-1 perturbations,

Reference 19

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:97f3874ae7d09a1574903ca738d5b56b7a0a3c3d79bbdec4dd8394be27e2558b

Observation cb581886-a45b-4696-a966-fd367bc74f87 · outbound

This paper cites OPFData: Large-scale datasets for AC optimal power flow with topological perturbations,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies OPFData: Large-scale datasets for AC optimal power flow with topological perturbations,

Reference 20

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:3caa7b55d760dee0a7c7ff866a4906ff62d074624a07b5aad2c438f8237097e4

Observation 8203d823-1754-4c59-8426-8780738fb614 · outbound

This paper cites Fast and reliable N-k contingency screening with input-convex neural networks,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Fast and reliable N-k contingency screening with input-convex neural networks,

Reference 21

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:7106771b8de0c03d21644be8169b298d3a9094287552ca4eef7dd958df9ebc56

Observation 08376e1e-4092-4f9b-9465-902118e2e28f · outbound

This paper cites PowerAgentBench-Dyn: A benchmark for agentic ai in power system dynamic studies,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies PowerAgentBench-Dyn: A benchmark for agentic ai in power system dynamic studies,

Reference 22

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:b07bcff6546c91f016340cbdb0c2eec7837e3d4b6158f405f3619572345b29df

Observation cc58d3d4-a0b5-41bb-8856-1cb676bc5ec4 · outbound

This paper cites Structural vulnerability assessment of electric power grids,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Structural vulnerability assessment of electric power grids,

Reference 23

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source=pdf_text observed=2026-06-26T19:54:36.660981Z digest=sha256:b4e7168a3827d481f8e5ef7d7bc88b7de52ee255108fce9ad2359ae483ed058b

Observation 22aa8f0d-88b8-4430-98d8-afdaad84efe8 · outbound

This paper cites Generalized contingency analysis based on graph theory and line outage distribution factor,.

PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies Generalized contingency analysis based on graph theory and line outage distribution factor,

Reference 24

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Pith citing papers

Observation cf68541e-de21-41d5-9bd1-6271b78e2364 · inbound

VeraGrid-Agent: Tool-Augmented LLMs for Distribution Optimal Power Flow at the Grid Edge cites this paper.

VeraGrid-Agent: Tool-Augmented LLMs for Distribution Optimal Power Flow at the Grid Edge PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies

Reference 12

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source=pdf_text observed=2026-08-01T03:19:18.585287Z digest=sha256:6e818e3ab84fc0304eb50d31ccc6ae7196944577a50f6bd21a1e72b0c78f0e2b