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Paper Citation Record · LEDGER

Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2312.12379.

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

pith.paper-citation-record.v1
2312.12379 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 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 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:41:22.234004Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:20:06.423412Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 92ccfeb8-581d-44e0-a88c-36170ec44607 · inbound

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models cites this paper.

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 12

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verified exact
arxiv_id, observed 2026-05-16T02:33:30.292836Z

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.

source=pdf_text observed=2026-05-16T02:33:30.143907Z digest=sha256:930b2b147edc860a7e7ae2fb0e6c416d237bc8df071251097f275aa8492a1f02

Observation 6fab4449-ee94-484b-96a5-0786bee9e9b1 · inbound

Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts cites this paper.

Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 13

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no resolver link, observed 2026-08-07T12:25:05.093737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:05.093737Z digest=sha256:7811974225f6f8c16c7b62e8dcb27d61fb2eaefafd178c308476fe85c123079d

Observation d046d532-f878-482a-ba56-fd7bf699edb0 · inbound

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping cites this paper.

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 30

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unresolved
no resolver link, observed 2026-08-07T11:32:06.772655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:32:06.772655Z digest=sha256:cc6add556f76ca653895c37f37c0c471555d8f258f919516ba438a31f4f0d375

Observation 96e8f015-cf40-45ae-a557-f1159dd9b5c7 · inbound

Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.

Cartridges: Lightweight and general-purpose long context representations via self-study Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 30

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unresolved
no resolver link, observed 2026-08-07T06:04:29.152331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:29.152331Z digest=sha256:c557e2a5fdf4e8b4dbfeb7fc8dcd6d0ee71c2a211699f51b92c0fa88ed9b2fde

Observation 3043e1a3-acaf-4f88-b146-36679aa7fc55 · 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 Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:51.320558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:51.320558Z digest=sha256:d66f24e448ede4e9074074785efbccefdbf4902898e1b94545afd96e7a5827f9

Observation b96378a5-0661-41fe-aa0e-e5076c7346d6 · inbound

Dynamic-DINO: Fine-Grained Mixture of Experts Tuning for Real-time Open-Vocabulary Object Detection cites this paper.

Dynamic-DINO: Fine-Grained Mixture of Experts Tuning for Real-time Open-Vocabulary Object Detection Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:36.504291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:54:36.504291Z digest=sha256:70244ba8c125e1565203a1c4200393a906db7088162e590828e0052ecc90d0e6

Observation f75f8036-1b95-49da-b06f-ff81f1fe2f31 · inbound

GRASP: Guided Residual Adapters with Sample-wise Partitioning cites this paper.

GRASP: Guided Residual Adapters with Sample-wise Partitioning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:58:55.104128Z

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.

source=pdf_text observed=2026-05-17T02:55:28.489534Z digest=sha256:b9341782ec376f1c53563fed37e21c74e503a1cfe7b778d7b1183684d08fc0e5

Observation a89d258e-9f42-40d1-ad52-55b0ac051282 · inbound

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation cites this paper.

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-16T19:11:11.498274Z

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.

source=pdf_text observed=2026-05-16T19:10:47.425041Z digest=sha256:01d2908466fd28c7d5d2e0f30250afee91c411692e5d4d5acf3992565e521c70

Observation 6d439733-d436-451d-8dca-4f2b0ddf9917 · inbound

ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics cites this paper.

ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 15

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unresolved
no resolver link, observed 2026-07-13T14:28:05.261852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T14:28:05.261852Z digest=sha256:efa59201ceb3b3492d823943fe6cd4945544a1413341067f48bb03e7e41be451

Observation 64772e1f-b2b4-4957-90d3-077476ddc25d · inbound

ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics cites this paper.

ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-15T11:44:19.622453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T11:44:19.622453Z digest=sha256:e30d06e1556d5abb5f40d35fe657e3b2c80ec2305a95a5bb4ae4e403693f5d34

Observation 95961ac8-9d37-4d97-8ab0-2d5c3ffe849c · inbound

Adapting 2D Multi-Modal Large Language Model for 3D CT Image Analysis cites this paper.

Adapting 2D Multi-Modal Large Language Model for 3D CT Image Analysis Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:20:58.213409Z

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.

source=pdf_text observed=2026-05-10T16:43:02.337806Z digest=sha256:11ec634a106b8af40ccf029b3d1574f939a58d17f2c8e5311015caf5bcf47a1a

Observation f26fa6ef-7f36-406f-9923-3b3d5282aa37 · inbound

Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework cites this paper.

Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:01:01.226101Z

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.

source=pdf_text observed=2026-05-10T15:42:17.370111Z digest=sha256:ba85f50d95c4b71781dba9b1570f0652e242adc054022b8b4135f1722f66bcc8

Observation 8b5a7f40-f767-4c9a-8622-a6f6570de8cf · inbound

AxMoE: Characterizing the Impact of Approximate Multipliers on Mixture-of-Experts DNN Architectures cites this paper.

AxMoE: Characterizing the Impact of Approximate Multipliers on Mixture-of-Experts DNN Architectures Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:50:40.085559Z

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.

source=pdf_text observed=2026-05-08T18:05:53.325249Z digest=sha256:0d8e9fccc52df7039bea2ad31e85cacabca93ad9bccd125d2acc98d783d85789

Observation 9ce70066-e52c-421a-b850-4a942cd0c5f4 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:26:26.794720Z

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.

source=pdf_text observed=2026-06-28T10:56:13.058872Z digest=sha256:e21ffaaad715cac1eb8d7bfe4fcb19c3cef86b7395d77c804b0e0faf5da408c8

Observation 8429b92f-d423-4be0-91ea-17abb19f6fbf · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 55

Resolution
unresolved
no resolver link, observed 2026-07-13T07:44:25.325808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T07:44:25.325808Z digest=sha256:ec003e6b07b2f20927ded201c85cf3806b828ce9e433a1270f4db0d092261e29

Observation d5385c8f-9ed0-4d64-b6e8-7708805504b3 · inbound

CogniRoute: Learning to Route Social Evidence in Omni-Modal Models cites this paper.

CogniRoute: Learning to Route Social Evidence in Omni-Modal Models Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 146

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metadata mismatch
arxiv_id, observed 2026-07-04T03:49:30.358412Z

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.

source=arxiv_source observed=2026-06-26T17:37:11.371892Z digest=sha256:1a2d0754b86a94ba2f3f6cfa1718f5262eee477625f340cbf538c2829024bbc7

Observation 221e1016-5712-4fd7-878c-db232786af95 · inbound

Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models cites this paper.

Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 82

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T06:39:37.877359Z

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.

source=arxiv_source observed=2026-06-26T14:18:11.215278Z digest=sha256:a26ad6e0ef6995edf0a2c9fee1af7bc0af7bdff1c056796f696666f17e771164

Observation bf317ea8-c20a-4cac-8406-4df09abc9e78 · inbound

Omni-Perception Policy Optimization for Multimodal Emotion Reasoning cites this paper.

Omni-Perception Policy Optimization for Multimodal Emotion Reasoning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 62

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:20:06.426079Z

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.

source=arxiv_source observed=2026-06-25T21:31:38.450382Z digest=sha256:0207e13948c9db1c74a6ae260f451fbc6555d07ca71fa363eb65effcd194b930

Observation 8db72ac7-ab21-4c16-a149-e4c005f9e49b · inbound

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models cites this paper.

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T15:39:56.513187Z

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.

source=pdf_text observed=2026-06-26T01:32:40.435742Z digest=sha256:cb6cba6274a8c2669d67fb2d64b9fb043cd4898bdf0da906e6ee6196fbfbcda6

Observation 92dcccf6-1b3d-4daf-b83e-13e22c557ed0 · inbound

MED-DSLC: Multi-Expert-Domain Classification via Domain Supervision and Logit Calibration cites this paper.

MED-DSLC: Multi-Expert-Domain Classification via Domain Supervision and Logit Calibration Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-14T07:52:08.823198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:52:08.823198Z digest=sha256:a46187ce907b1861889251d286e926e9cddb3d50a39eb64f98e0ac017099855a

Observation 54ab2b6e-1582-4b31-b96c-cde32a9df93b · inbound

SpecDrop: Parameter-Free Category-Conditioned Routing for Modular Specialization cites this paper.

SpecDrop: Parameter-Free Category-Conditioned Routing for Modular Specialization Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 2017

Resolution
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no resolver link, observed 2026-08-08T00:41:22.234004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:41:22.234004Z digest=sha256:0134f075de57e327fd8ac01ef8358a84edd0ce14304b0beaf3c759cb5ebc9e33