Paper Citation Record · LEDGER

LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2401.16160.

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

pith.paper-citation-record.v1
2401.16160 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 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 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:27:27.613944Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:37.931584Z

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 479eb45c-7444-405e-8877-fc7977743b7d · 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 LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T21:56:03.233940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d0a2219-df45-403c-a336-546f01181b40 · inbound

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment cites this paper.

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T19:35:30.155374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66132ade-bf2d-4a37-b9ba-22066cb3ef22 · inbound

From Holistic to Localized: Local Enhanced Adapters for Efficient Visual Instruction Fine-Tuning cites this paper.

From Holistic to Localized: Local Enhanced Adapters for Efficient Visual Instruction Fine-Tuning LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T17:37:54.701624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6164bfe4-553e-4a0e-954a-1ee7e3d32d9a · 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 LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T23:49:02.155342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d08e4eff-145f-4219-9bba-e1e4797e0588 · inbound

MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learning cites this paper.

MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learning LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:28.284426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a9e43a5-f4e5-409f-b179-afeb400b7982 · inbound

WalkVLM:Aid Visually Impaired People Walking by Vision Language Model cites this paper.

WalkVLM:Aid Visually Impaired People Walking by Vision Language Model LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:18.850612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd887de8-de48-40b5-a587-06747627b7ab · inbound

OMoE: Diversifying Mixture of Low-Rank Adaptation by Orthogonal Finetuning cites this paper.

OMoE: Diversifying Mixture of Low-Rank Adaptation by Orthogonal Finetuning LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T19:29:51.282697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af52773b-2255-4706-b754-74dbe8e86838 · inbound

Mixture of Experts (MoE): A Big Data Perspective cites this paper.

Mixture of Experts (MoE): A Big Data Perspective LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T18:56:37.206107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2d2d0da-7e76-4c93-933f-53743e5ca750 · inbound

Ensembles of Low-Rank Expert Adapters cites this paper.

Ensembles of Low-Rank Expert Adapters LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T20:29:52.457508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eae7506-b207-4624-99cf-17fcb78d4427 · inbound

On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation cites this paper.

On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T10:14:21.408391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb8170dc-8fdd-433b-bf5d-18d0d3472213 · inbound

Cached Multi-Lora Composition for Multi-Concept Image Generation cites this paper.

Cached Multi-Lora Composition for Multi-Concept Image Generation LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T21:03:23.601223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63d240c0-17eb-426c-84cc-121c493e4f32 · inbound

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models cites this paper.

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:30.667213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04fc078c-13e6-463e-be1b-fd4c8a7b8b1e · inbound

Topology-Assisted Spatio-Temporal Pattern Disentangling for Scalable MARL in Large-scale Autonomous Traffic Control cites this paper.

Topology-Assisted Spatio-Temporal Pattern Disentangling for Scalable MARL in Large-scale Autonomous Traffic Control LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T00:56:31.389481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecc81d5d-252c-4c36-856a-e5fbf090c530 · inbound

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE cites this paper.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T19:27:27.613944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1206979b-4d55-4c97-9687-9084d7322f15 · inbound

Little by Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts cites this paper.

Little by Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:06:34.578978Z

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.

Observation 4ea801d1-8082-4f14-918b-ce4876080bea · inbound

LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing cites this paper.

LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:07:14.590833Z

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.

Observation e25a6566-03fe-448e-b96e-1a18c33656c3 · 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 LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T14:54:35.744719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8cb6893-b11d-4218-ae00-7a428562779e · inbound

SpaceVista: All-Scale Visual Spatial Reasoning from mm to km cites this paper.

SpaceVista: All-Scale Visual Spatial Reasoning from mm to km LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T10:37:36.541791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a1970ee-14ae-40cc-8ecb-5cbf035598f0 · 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 LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 6

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d981c2b0-1579-4e31-8662-a8e9ca752156 · inbound

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

Reference 6

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3806b7d-7cd5-46cf-b089-e6dca75c75ac · inbound

SMoES: Soft Modality-Guided Expert Specialization in MoE-VLMs cites this paper.

SMoES: Soft Modality-Guided Expert Specialization in MoE-VLMs LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:41:13.409874Z

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.

Observation c3388595-118a-4c4c-8268-7edf4dbe0b8f · inbound

View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification cites this paper.

View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:18:13.787610Z

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.

Observation 806919f6-2888-4c0e-9ae0-0b82b09b7402 · inbound

Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models cites this paper.

Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:26:00.085135Z

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.

Observation a5793eb8-df3a-43ef-b26f-181320f43c72 · inbound

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models cites this paper.

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T06:56:44.610544Z

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.

Observation fc385657-91f6-4a50-b383-7cb5caefe239 · inbound

5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning cites this paper.

5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:17:37.222675Z

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.

Observation 2c4cb590-f8ab-4f88-b93a-92f1e8dc1652 · inbound

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

CogniRoute: Learning to Route Social Evidence in Omni-Modal Models LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 134

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:49:30.422426Z

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.

Observation f9cfa2d8-df0c-4f8b-b42d-2b3b828f958e · 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 LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 125

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T06:39:37.932817Z

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.

Observation bbca3588-d6a9-4186-a80b-ea0b09159c5f · inbound

Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory cites this paper.

Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T21:34:44.701020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.