Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.04735.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:55:09.184458Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T11:32:17.234492Z
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 a67517b0-0cf1-4783-a72d-355799084aa2 · inbound
From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.
From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
Reference 202
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T02:57:38.103704Z
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.
Observation db1cc2b3-e247-45b4-a223-2f6b9334f610 · inbound
To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems cites this paper.
To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:32:17.238094Z
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.
Observation 900a5ddc-6eee-4d37-8b18-4403bea9fd42 · inbound
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models cites this paper.
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:55:09.184458Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc48e546-6996-4223-bbff-d7709d37316c · inbound
Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System cites this paper.
Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:39:04.422234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.