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Paper Citation Record · LEDGER

LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.21227.

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

pith.paper-citation-record.v1
2503.21227 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:37.316578Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:26:23.226477Z

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 7b41c1be-a796-4c48-90f3-ac859a604942 · inbound

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

Reference 259

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:37.316578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:37.316578Z digest=sha256:f728f4fabf62f11b66692885d85f4880f25a1c63d4d5e1f0ef4bbf0b42630564

Observation 4190350e-92e2-4d81-876a-edb052bed67c · inbound

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning cites this paper.

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-03T05:33:14.911341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:33:14.911341Z digest=sha256:41e310a2fa688de711b469803ec0fea9b0e45aa3d59d12572e086c6162026a27

Observation 01ed2fc1-0677-48c5-974c-cd20ff67f287 · inbound

The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models cites this paper.

The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:15:50.112634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T20:04:46.144856Z digest=sha256:be891d77c8bfdc2348bc903bfb28df945d7c070226c5d8a46da728f360e4e0e9

Observation d4a43f89-c086-429d-84e2-67935bbd0ed7 · inbound

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning cites this paper.

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:26:23.228515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T14:18:11.452378Z digest=sha256:57788b29875cd9e56cdb967db2be3757e444ce2685c69c6477510a6d6d72a63d

Observation 63fde66b-62bd-49f7-b87f-0f07d9b13c52 · inbound

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning cites this paper.

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:36:18.004182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T15:09:00.320198Z digest=sha256:b2e6d132b36711a49121992362d16137bb73f9a438375efa3f6b02f33b0ffde7