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Paper Citation Record · LEDGER

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency

As of 7 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.12724.

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

pith.paper-citation-record.v1
2506.12724 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:47:50.404759Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0963f86-4b0f-4522-ab6f-31c2a357a002 · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 1

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unresolved
no resolver link, observed 2026-08-07T00:47:50.338627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 63157067-04a8-4578-be86-a399723a710e · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Flamingo: a Visual Language Model for Few-Shot Learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.343150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.343150Z digest=sha256:100533a62fc3d135c6b7ee24b81c3245e2a7aac71d357676413d0c769dec1713

Observation 8df1b59a-afa1-4117-8617-be392739b705 · outbound

This paper cites AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.347136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.347136Z digest=sha256:b68eb60d87b685d7fe39e1b340e4850c384e10efa586fc83b440c6db42c8e9e4

Observation 8cf80597-a52a-49c0-92c0-165faf9c3c61 · outbound

This paper cites Visual Instruction Tuning.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Visual Instruction Tuning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.351305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.351305Z digest=sha256:13502bfdbc6133ad9a75de49ce1620a792d893b17ef1073facdcf90298400fab

Observation 22a76260-dacd-4907-ab51-7bd2e730cf46 · outbound

This paper cites Learning transferable visual models from natural language supervision.ICML,.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Learning transferable visual models from natural language supervision.ICML,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.634602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.355500Z digest=sha256:7c87b8e6d992cad27e8438a66d7ae6474e2bc3d1c5047201101b3dc01179e1ae

Observation 2a59e8b0-f24f-41d5-bd05-2840cc8bee1f · outbound

This paper cites Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.362206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.362206Z digest=sha256:91838a0c431736f540afa05e612565f51b54e0045315bff9606c14f08c943d8d

Observation ed8536f1-1788-4ea7-ad09-fcb407202a97 · outbound

This paper cites Beyond dropout: Robust convolutional neural networks based on local feature masking.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Beyond dropout: Robust convolutional neural networks based on local feature masking

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.623042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.366641Z digest=sha256:b18246c169ff229800d4a6d05a2dc9ec53c40264cf5324ca04591841170d5bcf

Observation 6079d342-f93b-4f91-92a1-61c2daa5b5fd · outbound

This paper cites Adversarial Learning for Neural PDE Solvers with Sparse Data.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.370161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.370161Z digest=sha256:6475e93af20b35830e7806bc3ccbed33dc6f0909c5c6060067762057b42183d8

Observation 63d7a74c-6298-4dd6-b5de-b9284b4c3f49 · outbound

This paper cites Cross-modality perturbation synergy attack for person re-identification.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Cross-modality perturbation synergy attack for person re-identification

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.611560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.374112Z digest=sha256:2d4066519a572503eff77db4e7ef7d20f1c044fee2e94728f36355cfea20048f

Observation a3b4d717-b914-4da7-ac5f-9c12c7eae8c6 · outbound

This paper cites Person re- identification method based on color attack and joint de- fence.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Person re- identification method based on color attack and joint de- fence

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.598727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.377269Z digest=sha256:1ff11491f73874c59daa9e073addd115c98672a80a87934b5b9406b39d1134cc

Observation 2fcab2e8-ab84-403d-a4aa-6467d3bd12f1 · outbound

This paper cites Exploring Color Invariance through Image-Level Ensemble Learning.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Exploring Color Invariance through Image-Level Ensemble Learning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.380630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.380630Z digest=sha256:8d32db68b049e526fe867f09f11b5878b55f0019473e0f0cf43557a3ae5ab10d

Observation d56c0bef-0640-4c1f-bead-306941044f4e · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Gemini: A Family of Highly Capable Multimodal Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.384237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.384237Z digest=sha256:8a4b67b3c7be79bf2cad8c1c864e540ff11ccd9f797cee7b41470b2c6b323eaf

Observation a5ac239a-117d-4270-9e4d-9f27014e63a2 · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.587063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.388037Z digest=sha256:b8258758d1dcf59cc9a427fc843c8c34b4bc160d3cab3771e55f5f832aa6a3da

Observation 7d61dd35-6492-489b-87f5-e39c460889b4 · outbound

This paper cites Beyond augmentation: Empowering model robustness under extreme capture environments.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Beyond augmentation: Empowering model robustness under extreme capture environments

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.575020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.391228Z digest=sha256:4e46ce74af748f754502b8ee2378980411c22fad64226f2465c112dc787bb48b

Observation aeb203be-5b92-4b0d-adf6-6b8b06c9f952 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.ICML, 2016.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Dropout as a bayesian approximation: Representing model uncertainty in deep learning.ICML, 2016

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.564612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.394484Z digest=sha256:2284a3e8b677047a32e14a429e6c20b22b2e0276f96ccdc83a74d617335addfb

Observation 581db55a-9485-42fb-879b-bb5d41098147 · outbound

This paper cites Cross-Modality Attack Boosted by Gradient-Evolutionary Multiform Optimization.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Cross-Modality Attack Boosted by Gradient-Evolutionary Multiform Optimization

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:47:50.454735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.397605Z digest=sha256:33ce92ba7c3e7ebc5ed5bab3d6e98d1e8b7473ca7fdf03839c4fc739b48a0fb1

Observation 17e635bc-41fa-40bc-b221-7dd05fda1496 · outbound

This paper cites Gshard: Scaling giant models with conditional computation and automatic shard- ing.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Gshard: Scaling giant models with conditional computation and automatic shard- ing

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:47:50.554704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:47:50.401341Z digest=sha256:ebb903f441e94b94e0627cab02ad15177aee71363c01485ec645e738d67372ba

Observation 8b568bdd-c956-4ff0-8550-f4dff723ec8e · outbound

This paper cites FILIP: Fine-grained Interactive Language-Image Pre-Training.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency FILIP: Fine-grained Interactive Language-Image Pre-Training

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.404759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.404759Z digest=sha256:0b6a3ac65b4e6f0e46e6a2ee68fe1d079b50fd3bb843973749049dfd273f4703

Pith citing papers

No inbound Pith citation observations are available.