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Paper Citation Record · LEDGER

Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.08881.

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

pith.paper-citation-record.v1
2411.08881 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 2026-08-06T12:44:21.538622Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T07:26:01.111072Z

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 e3010720-da73-41a1-9bf6-9021a3d30020 · inbound

Evaluation and Benchmarking of LLM Agents: A Survey cites this paper.

Evaluation and Benchmarking of LLM Agents: A Survey Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:21.538622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:21.538622Z digest=sha256:0893ab5c21ebfd9b51028227e631821f66bf8e1c7d3b6a25f5e8e6c2b57ce726

Observation c1a9b8c7-2bcb-4180-bc1f-cc666aad1d18 · inbound

Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review cites this paper.

Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:26:01.113930Z

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=2026-05-10T17:11:23.553461Z digest=sha256:6f6273dda7873616d1d6b54f5abc5d3eeb9122a2a716b51104fc54bb2c99ba31