Paper Citation Record · LEDGER

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2412.15553.

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

pith.paper-citation-record.v1
2412.15553 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:24:12.322066Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:20:47.287787Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:20:48.264452Z

Reference resolution

38 of 38 outbound references displayed

verified exact0
verified fuzzy14
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8dd892e0-49e9-47e5-aaf9-fca97f8b33c6 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentral- ized Data,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Communication-Efficient Learning of Deep Networks from Decentral- ized Data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.985200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 81c58d05-ce2c-46e4-bd45-9774c0f8f120 · outbound

This paper cites Edge intelligence: The confluence of edge computing and artificial intelligence,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Edge intelligence: The confluence of edge computing and artificial intelligence,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.137734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c9b1a0-97b9-40b6-b217-d5df8696dfce · outbound

This paper cites Federated learning as a service for hierarchical edge networks with heterogeneous models,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Federated learning as a service for hierarchical edge networks with heterogeneous models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.956986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec7e2bc8-eba2-43ce-857f-0feb7c8bce0d · outbound

This paper cites Scaling distributed machine learning with the parameter server,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Scaling distributed machine learning with the parameter server,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.940474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 936aa78e-22f4-46db-932a-42d794b5911f · outbound

This paper cites Large scale distributed deep networks,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Large scale distributed deep networks,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.153004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 207a7bbe-43be-436c-919d-1666ea09f3dc · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Split learning for health: Distributed deep learning without sharing raw patient data,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.910944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4258a962-192c-4c66-92c2-d35d25fdfe2e · outbound

This paper cites Boosting communication efficiency of federated learning’s secure aggregation,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Boosting communication efficiency of federated learning’s secure aggregation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.892899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ed6adf2-4904-446c-913b-d13cbf65c849 · outbound

This paper cites Edge computing: Vision and challenges,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Edge computing: Vision and challenges,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.168596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a19c622e-146d-4b43-811d-5a70a482dccd · outbound

This paper cites Learning both weights and con- nections for efficient neural network,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Learning both weights and con- nections for efficient neural network,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.173470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59cc8b64-4e65-46c3-993d-3f5caa0152d6 · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.178461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ced6249b-160e-4c23-a9a5-1a7ead146add · outbound

This paper cites Distilling the Knowledge in a Neural Network.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Distilling the Knowledge in a Neural Network

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.183620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0edb36af-bfca-4d55-9beb-27af1d092551 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.188890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8597819f-a0a8-423c-9e9b-811531b8789c · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Universal Language Model Fine-tuning for Text Classification

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.193937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77367070-ff33-49cb-b1a5-090fa318fed2 · outbound

This paper cites Flocora: Federated learning compression with low-rank adaptation,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Flocora: Federated learning compression with low-rank adaptation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.853466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a58c172-a99b-42c0-9937-bbe030d036f8 · outbound

This paper cites QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.204095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04a30c73-d212-4a59-8416-3e59a66ded92 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Qlora: Efficient finetuning of quantized llms,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.209670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83f2720f-8d04-4db1-a8a9-50d6d39c430b · outbound

This paper cites FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.214484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e710e53-9b09-431a-945d-7043d09e7a9c · outbound

This paper cites Towards building the federatedgpt: Federated instruction tun- ing,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Towards building the federatedgpt: Federated instruction tun- ing,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.220108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 356db345-c091-46c4-a79f-5243bed3fcda · outbound

This paper cites Autoddl: Automatic distributed deep learning with near-optimal bandwidth cost,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Autoddl: Automatic distributed deep learning with near-optimal bandwidth cost,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.812999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f1a9ca29-1c59-4d05-9476-d398f9058ba5 · outbound

This paper cites OneFlow: Redesign the Distributed Deep Learning Framework from Scratch.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning OneFlow: Redesign the Distributed Deep Learning Framework from Scratch

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.229787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bd2e098-7fbc-45eb-ae6e-7209d29a4f0b · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.234285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e38ae0b-c49d-4e64-92a3-5c42e0e4c09c · outbound

This paper cites CURE: Privacy-Preserving Split Learning Done Right.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning CURE: Privacy-Preserving Split Learning Done Right

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.238912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e900ab8-1d5d-44db-b826-951d92c7d1c0 · outbound

This paper cites Fully homomorphic encryption using ideal lattices,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Fully homomorphic encryption using ideal lattices,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.243431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ead12568-9c71-40d2-ae32-0b64edf8677e · outbound

This paper cites Wainwright et al., Fundamental methods of mathematical economics.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Wainwright et al., Fundamental methods of mathematical economics

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.783283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 833609c3-92f6-4f41-a382-dd05b42c97c8 · outbound

This paper cites On the uniform convergence of relative frequencies of events to their probabilities,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning On the uniform convergence of relative frequencies of events to their probabilities,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.765383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5a482ef7-88b4-452f-b779-82ed64322c90 · outbound

This paper cites The elements of statistical learning: data mining, inference, and prediction,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning The elements of statistical learning: data mining, inference, and prediction,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.257757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85eccbf7-a56a-441d-b5c4-b8a3bac67b69 · outbound

This paper cites Opening the Black Box of Deep Neural Networks via Information.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Opening the Black Box of Deep Neural Networks via Information

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.262391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 285e4f12-369a-4bbf-a654-b343b403dc4e · outbound

This paper cites Explor- ing generalization in deep learning,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Explor- ing generalization in deep learning,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.267853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88e1dead-6b3e-4202-b582-9fd9d6f22438 · outbound

This paper cites Tzeng and J.-J.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Tzeng and J.-J

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.718147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 05d1562d-a93e-48d4-9561-23a456a03821 · outbound

This paper cites Determining objective weights in multiple criteria problems: the critic method,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Determining objective weights in multiple criteria problems: the critic method,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.279181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d28a2241-41ee-4212-b0fd-e1d40d44cd47 · outbound

This paper cites Learning multiple layers of features from tiny images,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Learning multiple layers of features from tiny images,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.284664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc9611ba-bc4c-4256-bc83-54ae735f82c5 · outbound

This paper cites CINIC-10 is not ImageNet or CIFAR-10.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning CINIC-10 is not ImageNet or CIFAR-10

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.289641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dccbd405-c044-4e97-905d-fe1c5ea91d40 · outbound

This paper cites pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.295405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8480338a-9d88-4d74-8c84-6e73e97a7a6b · outbound

This paper cites Federated fine-tuning of large language models under heterogeneous tasks and client resources,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Federated fine-tuning of large language models under heterogeneous tasks and client resources,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.682656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ebf3d61b-e16e-4699-ada9-9205d9b9f74e · outbound

This paper cites Rbla: Rank- based-lora-aggregation for fine-tuning heterogeneous models in flaas,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Rbla: Rank- based-lora-aggregation for fine-tuning heterogeneous models in flaas,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.663354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b4f1272-433a-4778-83c7-a0b6170861de · outbound

This paper cites Adam: A method for stochastic optimization,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Adam: A method for stochastic optimization,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.644730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2398b086-c0d2-431e-913d-0e92e4e77e90 · outbound

This paper cites Multiclass imbalance problems: Analysis and po- tential solutions,.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Multiclass imbalance problems: Analysis and po- tential solutions,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:12.626767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e40f270-63c9-4d4a-93f2-a3a246580875 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning Adam: A Method for Stochastic Optimization

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:12.316590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9098f3c6-2c81-4b34-9799-affbeedddb4b · inbound

AFLoRA: Adaptive Federated Fine-Tuning of Large Language Models with Resource-Aware Low-Rank Adaption cites this paper.

AFLoRA: Adaptive Federated Fine-Tuning of Large Language Models with Resource-Aware Low-Rank Adaption AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:20:48.359240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79a97fad-cb89-43b4-82ef-a5acf99d35e1 · inbound

DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models cites this paper.

DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T19:48:48.414653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.