Paper Citation Record · LEDGER

When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2310.18339.

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

pith.paper-citation-record.v1
2310.18339 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:06.433773Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:37.937049Z

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 5ba7cebb-9cb0-4d0b-bde7-0095f9ae8d8e · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:37.016483Z

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.

Observation 3b7fac65-ece0-4137-acb2-ed85b68c0b8b · inbound

Enhancing Multimodal Continual Instruction Tuning with BranchLoRA cites this paper.

Enhancing Multimodal Continual Instruction Tuning with BranchLoRA When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:09:06.433773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bdf4043-ac58-4559-abf6-d6b2ca1018a1 · inbound

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence cites this paper.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:49.397014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 581d6b9d-4afd-4a2f-84b3-e288088a9c76 · inbound

Mixture of LoRA Experts with Multi-Modal and Multi-Granularity LLM Generative Error Correction for Accented Speech Recognition cites this paper.

Mixture of LoRA Experts with Multi-Modal and Multi-Granularity LLM Generative Error Correction for Accented Speech Recognition When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T18:10:16.929883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78227526-7023-4df8-94a5-c76cabc8e162 · 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 When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:01:01.174261Z

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.

Observation 4613dd63-4db2-44ba-af7e-8bbed04adee0 · inbound

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning cites this paper.

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:36:09.050927Z

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.

Observation 919f1a62-b57c-4f33-974b-35455b88ae8b · inbound

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning cites this paper.

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:57.192179Z

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.

Observation a4b5bd5d-d9e7-4135-acf5-cdc22ddcf9c9 · 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 When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:17:37.210425Z

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.

Observation 73dc934d-1128-48c9-b356-631107c41eb8 · 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 When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 124

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T06:39:37.938446Z

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.

Observation 7fc1ab1d-cf9b-4f30-933a-a6f642b95c21 · inbound

Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning cites this paper.

Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:14:20.875090Z

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.

Observation 954b8664-5c7f-4a9f-bad1-fafd6c94bfcc · inbound

Progressive Multimodal Alignment for Continual Instruction Tuning cites this paper.

Progressive Multimodal Alignment for Continual Instruction Tuning When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-30T16:11:50.142318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ede99b5-d99b-4721-ad7f-2c4f4607df98 · inbound

Progressive Multimodal Alignment for Continual Instruction Tuning cites this paper.

Progressive Multimodal Alignment for Continual Instruction Tuning When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T01:24:02.123346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.