Paper Citation Record · LEDGER

Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.14093.

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

pith.paper-citation-record.v1
2407.14093 v3

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 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:02:16.470816Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:36:57.356695Z

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 8a20ff2a-cece-4070-bc03-06edff368251 · inbound

Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings cites this paper.

Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T06:04:22.036925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d772d0ca-3939-40d3-a7f7-1b8394918ccd · inbound

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs cites this paper.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T18:33:20.319719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06aa728c-9d30-43ab-8e2d-6a8b686423ee · inbound

Knowledge Grafting: A Mechanism for Optimizing AI Model Deployment in Resource-Constrained Environments cites this paper.

Knowledge Grafting: A Mechanism for Optimizing AI Model Deployment in Resource-Constrained Environments Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T18:02:16.470816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af9ad45a-d066-41fd-8e0f-5f5083bb7efb · inbound

CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering cites this paper.

CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:11:53.252508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7afca9cf-1c55-48cf-b367-9de6783b392e · inbound

AlignCultura: Towards Culturally Aligned Large Language Models? cites this paper.

AlignCultura: Towards Culturally Aligned Large Language Models? Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:56:04.912799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e6ae106e-6105-4167-9c58-76fb67702380 · inbound

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs cites this paper.

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:36:57.358290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.