Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.00557.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:02:43.427567Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T20:47:53.067967Z
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 0b7ea32b-b90d-49db-93ce-e1c47efb35a2 · inbound
RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting cites this paper.
RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:29:04.288994Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 648bc372-db72-460b-ba3d-ef72a90a9c22 · inbound
Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions cites this paper.
Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T19:07:35.381498Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51d270ad-c536-4e8a-af72-0792e07456e4 · inbound
Generative AI Act II: Test Time Scaling Drives Cognition Engineering cites this paper.
Generative AI Act II: Test Time Scaling Drives Cognition Engineering Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
Reference 207
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:02:43.427567Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a147fbc4-b2b4-4d37-bccc-a1719441284d · inbound
ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving cites this paper.
ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
Reference 22
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T20:47:53.149522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7a4cb6a6-a0e9-409c-8a5c-1cf83c18de0f · inbound
A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models cites this paper.
A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
Reference 142
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T10:39:07.000752Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.