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Paper Citation Record · LEDGER

LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2408.15881.

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

pith.paper-citation-record.v1
2408.15881 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:27:20.034849Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation acfa3182-69dd-4561-a30b-55dd8f13133e · inbound

Advancing Fine-Grained Visual Understanding with Multi-Scale Alignment in Multi-Modal Models cites this paper.

Advancing Fine-Grained Visual Understanding with Multi-Scale Alignment in Multi-Modal Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T20:27:20.034849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:27:20.034849Z digest=sha256:548ca845868329d932dca9fc0bcf3f4dc1d9d70a49f4952aad07fa37cbbca9f4

Observation a5b5d26a-1878-4011-ad18-6a00bb4f94fa · inbound

Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model Enhancement cites this paper.

Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model Enhancement LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T04:33:06.994664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:33:06.994664Z digest=sha256:53b734d5ff50a308d617f12ff7b127730cc14ee7d8a078d207d682f9abd87e18

Observation e505e7ca-399f-44ae-a671-5f0d2efe47f9 · inbound

A Survey on Inference Optimization Techniques for Mixture of Experts Models cites this paper.

A Survey on Inference Optimization Techniques for Mixture of Experts Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 163

Resolution
unresolved
no resolver link, observed 2026-08-11T12:44:35.970232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:44:35.970232Z digest=sha256:5935dd9282faddce60f05b707e394406cba5c5e38149318bd110d8ff89258839

Observation 1fb87df2-bf6a-4d24-86d2-b06f143106d1 · inbound

MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders cites this paper.

MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T22:27:13.611917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:13.611917Z digest=sha256:c8dbcd1a05510cac3bed6092a8a9a3de613f5d047f1223f3ed403c5f23139309

Observation 8dbb2853-d0f2-41ad-a8d6-9881a01f0b1d · inbound

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion cites this paper.

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T22:08:35.051307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:08:35.051307Z digest=sha256:0fb5ff4aeb53469a4411d298206c1c407e5da1dbe5ad2c1611a0d9f3adf5641a

Observation 02e740a3-e6a5-40af-9e5b-e2df760632d3 · inbound

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models cites this paper.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:07.514859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.514859Z digest=sha256:46fcd8542759e7f95b390b6933f606ccb2cf85ca56a8366af6d076c519a5bfac

Observation e5acd949-8072-4ba1-91a2-67b0f7a43217 · inbound

Taming LLMs by Scaling Learning Rates with Gradient Grouping cites this paper.

Taming LLMs by Scaling Learning Rates with Gradient Grouping LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:29.197574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:57:29.197574Z digest=sha256:e460a5f65e3f0547fa520c3de30f54e0bd807549ae75c828d672990bffa1d759

Observation d467dccd-ba5d-42c6-be9e-3dd45878b382 · inbound

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-06T23:57:25.601970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:57:25.601970Z digest=sha256:2aaa5af5d46a09822590c0d0e42327e70d12fc8b6a4968e2b077731ad035ff47

Observation 99b1b392-0dc2-4e2c-9b1c-36795ad393c0 · inbound

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards cites this paper.

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T21:09:24.726089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:09:24.726089Z digest=sha256:66770396429e04dd68bd1f7c1da34f3708d08287b00ea625ec3fa9496f9e07ac

Observation c331b021-49dd-449b-9275-653f29f25331 · inbound

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models cites this paper.

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:25:18.526409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T11:23:46.371799Z digest=sha256:1c1c6c620f79ac5c96e2e8f109a9750911ba4e5a03c9ea938910cef90573f134

Observation 5b68943e-0271-48d1-8a18-f01ccad88700 · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 214

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T23:54:45.348826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-09T23:51:47.724033Z digest=sha256:c0d77e28cf4c4e426af64ab270028ed9b77b90c9112d20e48b1ff782bbdf2173

Observation 52144856-6287-4cda-93d6-004ee972db3e · inbound

ViCuR: Visual Cues as Recoverable Privilege for Multimodal On-Policy Distillation cites this paper.

ViCuR: Visual Cues as Recoverable Privilege for Multimodal On-Policy Distillation LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:36:57.017799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T01:59:15.154873Z digest=sha256:8e5010e84b6ebe7c214eb4cb8165b3a301568f42487fbad2d0331d1b5072bf6d

Observation afb7bdd5-f0d4-4314-9070-1171eb84c3f4 · inbound

Adaptive Two-Stage Visual Token Pruning for Efficient Inference in Video-Language Models cites this paper.

Adaptive Two-Stage Visual Token Pruning for Efficient Inference in Video-Language Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T00:55:50.120232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:55:50.120232Z digest=sha256:e6a83182cb48793c610f17a9cd3da7650d4ee2da64fbb6f5e02e79015ab28d61