Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MoA is All You Need: Building LLM Research Team using Mixture of Agents
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.07487.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T18:11:28.101723Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T12:34:38.866552Z
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 c3860c71-e172-46a8-b888-aafa58327361 · inbound
Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial? cites this paper.
Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial? MoA is All You Need: Building LLM Research Team using Mixture of Agents
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:11:28.101723Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f16f154-00da-4599-86b9-4d9ab187a59c · inbound
SANet: A Semantic-aware Agentic AI Networking Framework for Cross-layer Optimization in 6G cites this paper.
SANet: A Semantic-aware Agentic AI Networking Framework for Cross-layer Optimization in 6G MoA is All You Need: Building LLM Research Team using Mixture of Agents
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T19:23:19.692503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation de9c038a-9a13-40d0-b209-d3a3f467840a · inbound
MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration cites this paper.
MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration MoA is All You Need: Building LLM Research Team using Mixture of Agents
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T12:34:38.868163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.