Paper Citation Record · LEDGER

Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.11273.

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

pith.paper-citation-record.v1
2405.11273 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:46:12.137924Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:14:20.899067Z

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 7ee4fd34-f493-45cf-93ec-be559e2e05e9 · inbound

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition cites this paper.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.137924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f5cf16c-76f7-4b7a-a3de-20e2dbd3525f · inbound

Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models cites this paper.

Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:33.747690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b46199-94d2-4feb-bef5-3db23da35655 · inbound

Neural Inhibition Improves Dynamic Routing and Mixture of Experts cites this paper.

Neural Inhibition Improves Dynamic Routing and Mixture of Experts Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T20:22:11.898319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 800b636e-a3e2-47da-b929-62c22976b28c · inbound

M3LLM: Model Context Protocol-aided Mixture of Vision Experts For Multimodal LLMs in Networks cites this paper.

M3LLM: Model Context Protocol-aided Mixture of Vision Experts For Multimodal LLMs in Networks Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T05:28:28.885000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 618b561e-c9cf-4349-a1fe-7f7863b0b02e · inbound

Decoding Visual Neural Representations by Multimodal with Dynamic Balancing cites this paper.

Decoding Visual Neural Representations by Multimodal with Dynamic Balancing Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:03.637569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e0cb1a2-c9a6-470b-8d7d-547f810f1ee9 · inbound

Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning cites this paper.

Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:14:20.900411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.