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Paper Citation Record · LEDGER

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices

As of 8 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 3 inbound Pith citation observations for arXiv:2507.23536.

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

pith.paper-citation-record.v1
2507.23536 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:41:43.354834Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T21:05:49.893508Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.844047Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7abae34a-8e4c-49ff-8064-91fc7aca51ea · outbound

This paper cites Invariant Risk Minimization.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Invariant Risk Minimization

Reference 1

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unresolved
no resolver link, observed 2026-08-06T10:41:43.297208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.297208Z digest=sha256:6a83d56740617da28f6ef9195e76ac9c976df1b0e583422e0d48d089faeb5e57

Observation b8b41b39-d450-4b67-a865-e89732f1ceaf · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 7

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unresolved
no resolver link, observed 2026-08-06T10:41:43.322565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.322565Z digest=sha256:c59097ea03a6ffa46576a28a1d754eaa1b57e076d9e23d40037a9cf62859b93b

Observation 9f1d0a16-d0d3-4413-977a-8a7d549b74cc · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 8

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unresolved
no resolver link, observed 2026-08-06T10:41:43.326513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.326513Z digest=sha256:caee175267e980ccd1291d2c8f6281917a09e6f7a5a75d24017bbf694edf9d82

Observation 18f15ff8-016f-42e5-b7c3-fa76ba51162a · outbound

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

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices LoRA: Low-Rank Adaptation of Large Language Models

Reference 9

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unresolved
no resolver link, observed 2026-08-06T10:41:43.330438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.330438Z digest=sha256:1d21822568fc58e39436fe1f4f778e585b1f2e1095078f70cf446d6c94ec6f97

Observation 54666b9c-e340-41d2-a94d-1114c778b4e5 · outbound

This paper cites The Entropy Enigma: Success and Failure of Entropy Minimization.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices The Entropy Enigma: Success and Failure of Entropy Minimization

Reference 11

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unresolved
no resolver link, observed 2026-08-06T10:41:43.338435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.338435Z digest=sha256:65163742e96f7ceaa7cc39ede0aacc5c691470c979c789401baed44e8069b567

Observation 79f04153-0c0f-443c-82cf-a0507b492e91 · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T10:41:43.346975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.346975Z digest=sha256:04ee29f245806b089b6ebdf98692762efe902744a0c90c418cd81cb692b52c8c

Observation ff35c07d-38ac-4c8c-99e8-ce245fbbd1eb · outbound

This paper cites GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 14

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unresolved
no resolver link, observed 2026-08-06T10:41:43.351113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.351113Z digest=sha256:cb909efd3b0f7686f1c70d5a40ea59309ecb0ba4dcb1f89ff8485eb1b2366a7f

Observation 79bb51d4-fd59-413b-acf1-bddcc9cc8385 · outbound

This paper cites Baseline hyperparameters for the analyzed PEFT methods, consistent with Hu et al.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Baseline hyperparameters for the analyzed PEFT methods, consistent with Hu et al

Reference 15

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T10:41:43.560736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T10:41:43.354834Z digest=sha256:89db06759e83fbda257251ea869f5c1f7616eea879890f621538ae2704d60dce

Observation 453e493e-63b1-4436-b3ab-1c15f72f6670 · outbound

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

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 2016

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unresolved
no resolver link, observed 2026-08-06T10:41:43.318235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.318235Z digest=sha256:1a2fc25425923956f063dcef146cdb395a771294f05bc62868cd40cfb46a1f2f

Observation 0f378383-931c-455b-9621-2d740a904059 · outbound

This paper cites Visual Wake Words Dataset.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Visual Wake Words Dataset

Reference 2017

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unresolved
no resolver link, observed 2026-08-06T10:41:43.305839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.305839Z digest=sha256:62b3e185443400b7ca82b16c12c762c8847f695e13d5f174b2a20abdc71c5349

Observation 024397ce-6bc8-4476-9a4b-75194ab49aaa · outbound

This paper cites Subspace-Configurable Networks.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Subspace-Configurable Networks

Reference 2018

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:41:43.416886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T10:41:43.342681Z digest=sha256:e4da1245efdc0bdc084c47ac33236eb12370becdb54b117c48d91b918e62ec04

Observation 5606ddbe-56b9-47e0-9d94-50832f18b549 · outbound

This paper cites REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints

Reference 2019

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:41:43.512438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T10:41:43.310034Z digest=sha256:ce0056cd185c21b104ef2fefae54cb0c0cd0564b835bec77ae154c6e04617839

Observation 803712bd-e059-4807-8bc7-ec547d522980 · outbound

This paper cites Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs

Reference 2021

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unresolved
no resolver link, observed 2026-08-06T10:41:43.313947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.313947Z digest=sha256:27e52e621784c8583707e44decbbd8f6637730eea8b5428f9d84e74e6c04d53c

Observation 80d3ebaa-e6f4-4f1d-b043-9dd20af342c9 · outbound

This paper cites SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models

Reference 2023

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unresolved
no resolver link, observed 2026-08-06T10:41:43.301828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.301828Z digest=sha256:bc112ec0dcc164322d8f2417a7f02c610feb4282777856c8196876f468aa0e7e

Observation 18891047-926f-49bc-9f86-8eee15e20a6e · outbound

This paper cites Test-Time Model Adaptation with Only Forward Passes.

From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Test-Time Model Adaptation with Only Forward Passes

Reference 2024

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unresolved
no resolver link, observed 2026-08-06T10:41:43.334161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:41:43.334161Z digest=sha256:7f5e5a59d1e230277d1e7580a68495c48e86fee3c92426280972ae79f4ea5f74

Pith citing papers

Observation 80ff85b3-15bb-468c-8b58-2e7b3b881f98 · inbound

On-Device Fine-Tuning via Backprop-Free Zeroth-Order Optimization cites this paper.

On-Device Fine-Tuning via Backprop-Free Zeroth-Order Optimization From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:05:21.441039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T22:03:53.594703Z digest=sha256:c26b29bee7302ff3d5db4ddfb347918d8f77ff63e690acb3f69abcf06f23072a

Observation cf8fc0b1-fc8d-4cf8-aaa4-74f0191a37aa · inbound

DAT: Dual-Aware Adaptive Transmission for Efficient Multimodal LLM Inference in Edge-Cloud Systems cites this paper.

DAT: Dual-Aware Adaptive Transmission for Efficient Multimodal LLM Inference in Edge-Cloud Systems From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:10:51.693536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T19:18:27.764572Z digest=sha256:f34e160178e280f403409f657dc0b84b3b526faed134159c028de9b535d345e1

Observation 827b0643-c07b-480f-a64f-13cfdbd925af · inbound

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices cites this paper.

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices

Reference 13

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metadata mismatch
arxiv_id, observed 2026-07-04T00:39:16.845468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T21:05:49.893508Z digest=sha256:86700de1f013fbf764e5f107700d6d5559eb77e84a3400362515f8b5c7c97b27