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Paper Citation Record · LEDGER

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

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 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

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measured 33 of 33 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:36:50.305511Z

measured 0 of 1 external citation measurements

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

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Outbound references

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 65c5cbad-1998-4907-a75f-9e03c3fa2800 · inbound

PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model cites this paper.

PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 22

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source=arxiv_source observed=2026-08-12T21:56:03.297496Z digest=sha256:5eba7d9bb1c1d2aeb7bc39edf2c3e9294e716262f57acf80f7e530c49dbc454d

Observation 3c3f3994-b778-4d62-958b-ef30bcac1c3c · inbound

Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts cites this paper.

Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 6

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Observation 3a5cfea1-a164-4dee-85f4-03bfbe566e60 · inbound

SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning cites this paper.

SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 9

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no resolver link, observed 2026-08-12T15:46:29.570019Z

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source=pdf_text observed=2026-08-12T15:46:29.570019Z digest=sha256:b63e7ac1343764d891a799010341a6244ba63fe3578ef318e9b153bb6b528863

Observation 49fb10d7-2997-454a-88fa-a598d0446a06 · inbound

On the Role of Discrete Representation in Sparse Mixture of Experts cites this paper.

On the Role of Discrete Representation in Sparse Mixture of Experts Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 22

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no resolver link, observed 2026-08-12T10:18:10.141045Z

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source=arxiv_source observed=2026-08-12T10:18:10.141045Z digest=sha256:80dee34d0205417801820f66845a704d8e49b59324ea36fef9065fe6ddaa0a21

Observation 3df9cc27-a4e3-4023-aa38-fa02beff9771 · inbound

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs cites this paper.

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 18

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no resolver link, observed 2026-08-11T23:49:02.231977Z

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Observation 8d38ea98-087b-433c-be53-866f026a45cf · inbound

SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts cites this paper.

SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 31

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no resolver link, observed 2026-08-11T20:40:39.505611Z

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source=pdf_text observed=2026-08-11T20:40:39.505611Z digest=sha256:2d33a3e2f48923a5e78420534cf9723ce6d4cf26a9e398fa5ec4a69039ebada2

Observation cf289185-7c2b-4bc4-9141-136d3753f6f9 · inbound

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning cites this paper.

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 31

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no resolver link, observed 2026-08-11T17:48:13.383661Z

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Observation 65c7b500-642c-474e-8abd-1da7b996eaee · inbound

RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting cites this paper.

RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 17

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source=pdf_text observed=2026-08-11T04:29:04.242534Z digest=sha256:342a07efd8d672a677e2733d744d01248d924d131b4bdd3d3600bb14a4292ae6

Observation e5be7f96-2041-4de9-a4a7-7bc81c2ecc2b · inbound

Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models cites this paper.

Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 17

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no resolver link, observed 2026-08-10T22:28:32.280679Z

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source=pdf_text observed=2026-08-10T22:28:32.280679Z digest=sha256:37d8ccb0d8bee4a097814753ded7943a5755b73a7541129ae7624d1953053fe3

Observation bbdb1794-01e2-40f7-ac60-8add2876eab5 · inbound

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning cites this paper.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 89

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Observation 330c7b39-7a2d-4561-a535-c75dbba72d11 · inbound

Ensembles of Low-Rank Expert Adapters cites this paper.

Ensembles of Low-Rank Expert Adapters Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 27

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no resolver link, observed 2026-08-09T20:29:52.518494Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:29:52.518494Z digest=sha256:a77634dd0288866991b91054a65902963734ab31733291050cd087f9e95db91e

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

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source=pdf_text observed=2026-08-07T12:25:05.093737Z digest=sha256:ade166bdb278fec70e4db4a400ec088ea0215c62311de687b30b15c283ffc662

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

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source=pdf_text observed=2026-08-07T11:32:06.772655Z digest=sha256:cf58cabf53d14d20fb02388fd5bfdc322755b04449b73b5155d0ec1f4530443f

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

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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

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

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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

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Observation 8d6dc96b-e6bb-470b-90fa-1533a46f0918 · inbound

Mixture-of-Clustered-Experts: Advancing Expert Specialization and Generalization in Instruction Tuning cites this paper.

Mixture-of-Clustered-Experts: Advancing Expert Specialization and Generalization in Instruction Tuning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 18

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source=arxiv_source observed=2026-08-15T16:36:50.305511Z digest=sha256:da31646c327aaaf41cb229f3c2cf56a70ef2ec65344c3efcd7b37bcbe49c27ec

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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

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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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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

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

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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

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-26T17:37:11.371892Z digest=sha256:469277ff3557463272d22b76b5561cf4475f0fb3cdf7c22cf834e24ea13b1887

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

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-26T14:18:11.215278Z digest=sha256:b286240b19f2b2fa82643fa82b9a5273113f428e2d0a1cf87eef60b25150ddbb

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

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-25T21:31:38.450382Z digest=sha256:640912e23c83ff1053c98c6e39aab76109a389e56574c3a58e2400811419bd4c

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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T01:32:40.435742Z digest=sha256:4ebb58d364828bd339c59cd609bb05eff5dd44f6596528c487b7a39b906444ca

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

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:52:08.823198Z digest=sha256:2e5ffa6c12a15c50a2f6ebdf43d06613f8cb8aab8b8963811c1e54a532448eba

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

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

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source=pdf_text observed=2026-08-08T00:41:22.234004Z digest=sha256:e198c07d44d9842652da8deab49b4eefa2eff5c676f0a553b5fc01a95fba4feb