Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:59:03.657419Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 100 of 109 outbound references and 0 inbound Pith citation observations for arXiv:2507.01438.
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 2026-08-06T20:59:03.657419Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 109 outbound references displayed
External citation measurements
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Observation 155a4a9a-86c1-4f36-8549-c55b3f5a1e80 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Reference 1
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Observation 9733a787-e914-40ae-9428-03732befad00 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Towards a Human-like Open-Domain Chatbot
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Observation 5c7af1b7-b74f-4ab7-877b-defe0adecebc · outbound
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Reference 3
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Observation 5fa49fe0-f239-4c90-b32c-817b60a264f0 · outbound
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Reference 4
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Observation 4d43623f-5c82-4dd4-a34d-e46eaa4c9d66 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LoRA Learns Less and Forgets Less
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Observation 1798d89a-d376-4af4-8b38-9992595268c0 · outbound
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Observation 5c3fd7f8-5c47-47e4-bbc8-e51daa8b4c32 · outbound
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Observation 1a229013-a723-48df-a265-7b52cfae57f2 · outbound
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Reference 8
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Observation e69981a7-2ec7-4c7c-8a6d-c1bc12034ac9 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Language Models are Few-Shot Learners
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Observation 05cbaa60-6614-46c1-b161-e736e89aa65a · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
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Observation 18998b76-9630-4786-95ba-8b0c1b63f62d · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation
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Observation ec579f46-5a3a-426f-8c43-d7b01002b4ca · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
Reference 12
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Observation e6150b3d-d79a-4eb4-b573-6f1538b83ca7 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Punica: Multi-Tenant LoRA Serving
Reference 13
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Observation 38107059-deff-4489-b49d-3d9c4e133fdc · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Reference 14
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Observation 41c65450-5ac0-49ab-9744-0a9f172974f8 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 15
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Observation e3715fe2-8cca-438e-8358-2809d9854531 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 16
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Observation 544b5aa5-0369-48d7-8cd4-8f1081a0ce08 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 17
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Observation 9e373ff4-4a20-4486-ae7a-7ae8ded09fab · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 18
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Observation e7001b7d-2f6e-4c04-84bc-b03df58cb9b4 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 19
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Observation e76af152-e7de-4a3a-bd2b-e8419b7fb046 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 20
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Observation 3ceaa933-54b8-4bfe-8f52-71b75092b9c5 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 21
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Observation 82f1dc8e-f75a-41ec-a563-6ac4bb7191fc · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
Reference 22
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Observation f2c6b3aa-806b-4b6b-9e05-fc585e927ca1 · outbound
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Reference 23
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Observation eee4ed60-70f2-4687-8696-449efbefd1a7 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 24
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Observation 4cd7b491-ea86-4dea-b954-9282756ee8d1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 25
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Observation dc773c05-af7f-483e-8f26-a00cc3dd7477 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices MultiModal-GPT: A Vision and Language Model for Dialogue with Humans
Reference 26
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Observation 8115d255-c229-447b-8901-002a575d3def · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices The Llama 3 Herd of Models
Reference 27
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Observation c72e5ab9-4a99-4369-9e96-6c2059d651df · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 28
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Observation f36efb7b-2958-4216-b7d7-52231ece2967 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
Reference 29
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Observation fe27a31d-715e-433e-bc60-a1b3c65db538 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Measuring Mathematical Problem Solving With the MATH Dataset
Reference 30
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Observation 4b72408a-2209-47e6-95be-27fddf4cd7a7 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 31
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Observation efe6693e-acff-498a-a6f2-9b4374b46997 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 32
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Observation 5849ed9a-0349-495f-8b30-558199302020 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LoRA: Low-Rank Adaptation of Large Language Models
Reference 33
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Observation b1ddc4d3-654a-4657-85ab-b212e8f835ab · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Mixtral of Experts
Reference 34
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Observation 7d13410d-f661-4ceb-8aa7-169602a8454e · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Lion: Adversarial Distillation of Proprietary Large Language Models
Reference 35
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Observation e21fba61-d5ed-461a-a18d-45cc7bd48ac6 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 36
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Observation a1585906-a585-4c36-ba80-a4a35718b074 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 37
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Observation 95e5cbd2-ae0f-435f-967b-061f9696e90e · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 38
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Observation 438bb62b-d495-4a96-bf0c-6cda7f240d2e · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices 2024.{InfiniGen}: Efficient generative inference of large language models with dynamic{KV} cache management
Reference 39
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Observation edd55d40-b4e5-4816-a4b8-c636f39e2d4f · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices The Power of Scale for Parameter-Efficient Prompt Tuning
Reference 41
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Observation 62002a72-a1a7-4d74-844f-99082af9aa95 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
Reference 42
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Observation 8ea84793-3076-4305-b2fe-9514efb41ddd · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Prefix-Tuning: Optimizing Continuous Prompts for Generation
Reference 43
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Observation 55d7d7a6-14ce-4031-ad9f-c63106a2d612 · outbound
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Reference 44
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Observation ee5dda58-e335-4e86-a82c-1e4fe8db64e6 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Reference 45
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Observation 1b40480a-7ea3-4213-81db-144480da9d31 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 46
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Observation 6755b5cc-b0c7-4c82-aec5-3069666138e5 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LLM-grounded Video Diffusion Models
Reference 47
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Observation 406f14ba-feeb-476d-8a50-0296be30b8cb · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 48
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Observation 81319f9c-33c6-4cb6-8776-f0a7163ed375 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Tasks
Reference 49
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Observation 571983aa-256e-4f56-b96c-68a11dfe7ae9 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Reference 50
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Observation c9cec157-f1d6-4b48-9140-2eb43236a41c · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 51
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Observation 1606c9ea-83a9-4a69-8a6e-0b73634c7ee4 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 52
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Observation 45f82f12-538a-49ed-8601-d97a8e587845 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 53
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Observation 0eae0b1a-b32d-45bb-a672-f07a29daff20 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 54
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Observation 3af90498-5a8a-482a-8ae5-6955c5773bf9 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices OpenELM: An Efficient Language Model Family with Open Training and Inference Framework
Reference 55
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Observation 258b5983-38aa-4e5e-bd76-b87dabb5a8b8 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Empower Vision Applications with LoRA LMM
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Observation 13006e3a-7a8f-4ee6-8f21-75a1b91ab756 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 57
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Observation 4a22c84d-7f65-4d9e-823f-580bd864ff0a · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices 2023-2025
Reference 58
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Observation 10f8ed8f-07b3-40ee-867d-f7a6094ee9f4 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 59
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Observation 13037068-1147-4ec9-b577-6d44952ada5d · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond
Reference 60
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Observation a4ca4d0d-7009-4dc3-ad21-0b9ba0ee494c · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices GPT-4 Technical Report
Reference 61
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Observation 55f0130c-498d-4e35-be18-df2c4fcdec97 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Zhang, Mark Harman, and Meng Wang
Reference 62
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Observation 617744f1-b7c5-4193-8285-d9b8a8c1e0e1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers
Reference 63
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Observation 5d0d6566-cfa8-492e-bf01-5a959911f2ec · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 64
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Observation c2f2d3a9-42af-4563-9be1-6aff78b6f5e1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 65
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Observation de4af2ae-759e-410b-a46a-d88c424af820 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices GPQA: A Graduate-Level Google-Proof Q&A Benchmark
Reference 66
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Observation 6fbaf9a2-be3d-4cb9-9c08-c5618b31e11e · outbound
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Reference 67
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Observation 1269a875-dcdb-4f9f-89f1-f425a63affff · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Reference 68
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Observation baef3bd7-a0fa-4cc6-a9f9-3330b9945417 · outbound
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Reference 69
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Observation 855648a5-7807-46ce-a69d-bafa5bab2e8e · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 70
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Observation a5b6eea1-bc57-44ca-9cab-ee12f7df98f1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LLaSM: Large Language and Speech Model
Reference 71
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Observation ed9e4cf3-a4d7-43b7-9502-f11478102146 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Code Llama: Open Foundation Models for Code
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Observation 19b3b77a-05de-49b5-bdc2-eff859c31c48 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 73
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Observation d580ae2e-c08a-4398-9254-a1a722f9e353 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Llumnix: Dynamic Scheduling for Large Language Model Serving
Reference 74
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Observation ea9eaf75-cb4a-44b5-a548-0e5743f88284 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Reference 75
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Observation 99c10f8b-f9d6-470e-b478-4f57d1c909d4 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Reference 76
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Observation 1f7a281f-9fed-41cb-b0d0-0793ef5cc9aa · outbound
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Reference 77
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Observation 28de88fc-46bb-42ff-940c-1ae6e1dfb9e5 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 78
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Observation edf136a0-c492-4b58-9058-bc9d47281df1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
Reference 79
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EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices LLaMA: Open and Efficient Foundation Language Models
Reference 80
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Observation 3e159eb2-5cf8-49a5-89ac-a2603f76b23c · outbound
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Reference 81
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Observation 43045b74-7746-4ac7-b03f-8e40d37c2796 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Reference 82
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Observation 55d8775e-f13c-457a-aa20-3a4da6df49f1 · outbound
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Reference 83
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Observation d0242b78-1758-43a1-b7a2-0571493f61ee · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Gemini: A Family of Highly Capable Multimodal Models
Reference 84
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Observation 23ff07f6-ccb0-43f3-beb1-d05a180084db · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
Reference 85
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Reference 86
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Observation 49873064-557f-4ee1-962f-ff87032bc9c1 · outbound
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Unresolved cited work
Reference 87
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Observation 1c18de58-1efa-4ba3-9f79-c0959f7fe3db · outbound
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Reference 88
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Reference 89
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