Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:26:48.395288Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 2 inbound Pith citation observations for arXiv:2501.15361.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:26:48.395288Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:42:45.995786Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T09:49:44.470502Z
85 of 85 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation dc2c9e3a-0db4-48b5-b407-34d69d74d7a7 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models GPT-4 Technical Report
Reference 1
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Observation c6e2396a-c779-4b9b-9459-5c48b2181fb1 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models LLaMA: Open and Efficient Foundation Language Models
Reference 2
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Decentralized Low-Rank Fine-Tuning of Large Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 3
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Decentralized Low-Rank Fine-Tuning of Large Language Models On the Opportunities and Risks of Foundation Models
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Decentralized Low-Rank Fine-Tuning of Large Language Models Attention is all you need,
Reference 5
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Observation bac3bc96-d5e5-4304-8901-df7f974485db · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Universal Language Model Fine-tuning for Text Classification
Reference 6
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Decentralized Low-Rank Fine-Tuning of Large Language Models Parameter-efficient transfer learning for nlp,
Reference 7
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Decentralized Low-Rank Fine-Tuning of Large Language Models The power of scale for parameter-efficient prompt tuning,
Reference 8
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Decentralized Low-Rank Fine-Tuning of Large Language Models LoRA: Low-Rank Adaptation of Large Language Models
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Decentralized Low-Rank Fine-Tuning of Large Language Models Parameter-efficient fine-tuning of large-scale pre-trained language models,
Reference 10
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Observation 546f6a61-ff0d-43ad-8759-6b9bd48253dd · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Federated multilingual models for medical transcript analysis,
Reference 11
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Decentralized Low-Rank Fine-Tuning of Large Language Models Federated Learning of Medical Concepts Embedding using BEHRT
Reference 12
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Decentralized Low-Rank Fine-Tuning of Large Language Models Communication-efficient learning of deep networks from decentralized data,
Reference 13
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Observation b9867b81-ffc7-4a29-b54c-c0b6b79383aa · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Fedpetuning: When federated learning meets the parameter-efficient tuning methods of pre-trained language models,
Reference 14
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Observation a727df8b-2132-41f1-8dfa-e4199733ad60 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models
Reference 15
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Observation 80c4fd20-ac24-42df-9454-cdaf49f164cf · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Fedprompt: Communication-efficient and privacy- preserving prompt tuning in federated learning,
Reference 16
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Decentralized Low-Rank Fine-Tuning of Large Language Models Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models
Reference 17
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Observation 954dc0b7-9727-4ff5-97c8-fc042d3dee23 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
Reference 18
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Observation 62b003e6-dd0e-4a66-bc62-886f563e4611 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition
Reference 19
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Observation cbbeede9-7d39-48bb-8ad4-e552ef5af637 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Heterogeneous lora for federated fine-tuning of on-device foundation models,
Reference 20
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Observation 517a7ba1-f2a3-4908-b66b-aaa996803aa3 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
Reference 21
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Decentralized Low-Rank Fine-Tuning of Large Language Models FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
Reference 22
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Decentralized Low-Rank Fine-Tuning of Large Language Models Federated LoRA with Sparse Communication
Reference 23
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Observation 11fa83cd-1f74-428f-a42e-5a0a638dacbf · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Improving LoRA in Privacy-preserving Federated Learning
Reference 24
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Decentralized Low-Rank Fine-Tuning of Large Language Models Robust federated finetuning of foundation models via alternating minimization of LoRA,
Reference 25
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Decentralized Low-Rank Fine-Tuning of Large Language Models Decentralized federated learning: A survey and perspective,
Reference 26
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Decentralized Low-Rank Fine-Tuning of Large Language Models Large Language Model based Multi-Agents: A Survey of Progress and Challenges
Reference 27
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Decentralized Low-Rank Fine-Tuning of Large Language Models Scalable multi-robot collaboration with large language models: Centralized or decentralized systems?,
Reference 28
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Observation ac378c11-460c-48da-8118-fa4accef2f4c · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning,
Reference 29
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Observation a4d6dc44-8bdf-42c6-a638-a5947babc93e · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Personalized Federated Learning: A Meta-Learning Approach
Reference 30
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Observation 30a8dcb6-a53d-4dea-8a2a-b767e2af4d0a · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Tackling the objective inconsistency problem in heterogeneous federated optimization,
Reference 31
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Decentralized Low-Rank Fine-Tuning of Large Language Models Accelerating gossip sgd with periodic global averaging,
Reference 32
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Decentralized Low-Rank Fine-Tuning of Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 33
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Decentralized Low-Rank Fine-Tuning of Large Language Models Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models,
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Reference 35
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Decentralized Low-Rank Fine-Tuning of Large Language Models Peft: State-of-the-art parameter-efficient fine-tuning methods
Reference 36
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Decentralized Low-Rank Fine-Tuning of Large Language Models GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Reference 37
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Decentralized Low-Rank Fine-Tuning of Large Language Models Qlora: Efficient finetuning of quantized llms,
Reference 38
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Reference 39
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Reference 40
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Reference 42
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Decentralized Low-Rank Fine-Tuning of Large Language Models DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Reference 43
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Reference 44
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Decentralized Low-Rank Fine-Tuning of Large Language Models Towards a Unified View of Parameter-Efficient Transfer Learning
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Decentralized Low-Rank Fine-Tuning of Large Language Models Prefix-Tuning: Optimizing Continuous Prompts for Generation
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Decentralized Low-Rank Fine-Tuning of Large Language Models Parameter-Efficient Fine-Tuning without Introducing New Latency
Reference 48
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Decentralized Low-Rank Fine-Tuning of Large Language Models DoRA: Weight-Decomposed Low-Rank Adaptation
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Reference 52
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Reference 54
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Decentralized Low-Rank Fine-Tuning of Large Language Models Federated learning for connected and automated vehicles: A survey of existing approaches and challenges,
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Decentralized Low-Rank Fine-Tuning of Large Language Models Spreadgnn: Decentralized multi-task federated learning for graph neural networks on molecular data,
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Reference 67
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Reference 75
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Decentralized Low-Rank Fine-Tuning of Large Language Models The largest eigenvalue of sparse random graphs,
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Reference 78
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Reference 79
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Reference 80
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Observation 209e60ff-3e11-42b0-a8ae-7f5e9e63dc5d · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Fine-Tuning Language Models with Just Forward Passes
Reference 81
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Observation df092da4-fabb-4c35-a61f-11c6a3ca7485 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models On the convergence of decentralized gradient descent,
Reference 82
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Observation 719af4c3-ef4f-4bf7-933c-f5e9137942c5 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Decentralized gradient tracking with local steps,
Reference 83
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Observation 3e87e0f5-0538-4b0e-804b-e8b4e23faf4b · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Robust decentralized learning with local updates and gradient tracking,
Reference 84
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Observation 5835ae83-ef97-4365-b256-474bd4d40ae3 · outbound
Decentralized Low-Rank Fine-Tuning of Large Language Models Unresolved cited work
Reference 85
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Observation 3906c495-d8b2-43a7-8a2d-7ab7f898c474 · inbound
DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models Decentralized Low-Rank Fine-Tuning of Large Language Models
Reference 11
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Observation f1c7de4f-cd57-4c93-99be-c63d5761959f · inbound
Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning Decentralized Low-Rank Fine-Tuning of Large Language Models
Reference 52
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