Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2411.03284.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:12:35.827163Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T17:35:44.199771Z
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 fb75e794-6fa8-4052-9827-b26625e5061e · inbound
A Survey on LLM-as-a-Judge cites this paper.
A Survey on LLM-as-a-Judge SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T17:35:44.204299Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 033928a1-74e0-4388-a982-e9f5a9e1f9d1 · inbound
The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants cites this paper.
The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:12:35.827163Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f67615ef-5366-4947-a05b-f5a7327e10e0 · inbound
MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs cites this paper.
MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:23:58.917129Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 065edb2c-6337-4c27-b62e-6ffbc0d040f6 · inbound
How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs cites this paper.
How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:12:58.768620Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed5823d3-acbb-425b-a2bc-49ac35cae20f · inbound
Towards Cognitive Synergy in LLM-Based Multi-Agent Systems: Integrating Theory of Mind and Critical Evaluation cites this paper.
Towards Cognitive Synergy in LLM-Based Multi-Agent Systems: Integrating Theory of Mind and Critical Evaluation SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:15:05.309996Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8aee4ce5-d632-4ebb-aad9-0aaaf1399aae · inbound
S-AI-Recursive: A Bio-Inspired and Temporal Sparse AI Architecture for Iterative, Introspective, and Energy-Frugal Reasoning cites this paper.
S-AI-Recursive: A Bio-Inspired and Temporal Sparse AI Architecture for Iterative, Introspective, and Energy-Frugal Reasoning SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T06:45:11.190127Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cfb6be75-6a08-4b86-8c6d-d723df06f34e · inbound
Chained Recursive Language Models for Multi-Iteration Reasoning cites this paper.
Chained Recursive Language Models for Multi-Iteration Reasoning SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T04:47:19.356870Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.