Paper Citation Record · LEDGER

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

As of 17 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 2026-08-17T06:30:58.91139+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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified exact; 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 2026-08-17T06:30:58.91139+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-06-26T19:54:36.660981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-01T03:19:18.585287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.