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Paper Citation Record · LEDGER

Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2402.04401.

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

pith.paper-citation-record.v1
2402.04401 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:36:18.462263Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T01:09:19.444029Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 fc76898a-6ecb-463b-bfb8-a14692a4165a · inbound

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond cites this paper.

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 6

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verified exact
arxiv_id, observed 2026-05-23T21:48:28.698884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T21:47:28.193374Z digest=sha256:76323f37fa9d1d5ace6590514166b971da43394e71d9e93d96e769ced1ac309a

Observation 80a0b915-b372-4e14-aa96-cf30255f137e · inbound

On the Way to LLM Personalization: Learning to Remember User Conversations cites this paper.

On the Way to LLM Personalization: Learning to Remember User Conversations Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 52

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no resolver link, observed 2026-08-12T16:32:05.002810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:32:05.002810Z digest=sha256:0f5cbb097df83e9042b108e5dd52da7a9be74c5aa3356b5140a5e0504f23e715

Observation c3e1c07f-64af-4067-8932-d401a14bc506 · inbound

DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users cites this paper.

DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 45

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no resolver link, observed 2026-08-12T10:50:51.687330Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:50:51.687330Z digest=sha256:79721bffe9520ee31962153e2205ce06e7684c5ddffa36b63ed61126b783f2c3

Observation 82638d57-f78c-46ab-8a9c-edcde57147ad · inbound

Multi-Dimensional Insights: Benchmarking Real-World Personalization in Large Multimodal Models cites this paper.

Multi-Dimensional Insights: Benchmarking Real-World Personalization in Large Multimodal Models Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 58

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unresolved
no resolver link, observed 2026-08-11T13:58:43.692882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:58:43.692882Z digest=sha256:61e922981e821c9acdb74620ef80dfb6d3a23d0d4b11c41e41652b96e906e155

Observation 826f8cfc-7bf9-45b1-a85e-e890edfcb377 · inbound

AI PERSONA: Towards Life-long Personalization of LLMs cites this paper.

AI PERSONA: Towards Life-long Personalization of LLMs Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 30

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no resolver link, observed 2026-08-11T13:31:41.378412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:31:41.378412Z digest=sha256:4d47598f4b7aea966d3a2f022ea335f9e06f47e1982d74ea971b931da3bb679e

Observation 8c7c15b7-8f98-4c13-a872-0054fc998516 · inbound

Can Large Language Models Understand Preferences in Personalized Recommendation? cites this paper.

Can Large Language Models Understand Preferences in Personalized Recommendation? Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 47

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unresolved
no resolver link, observed 2026-08-10T16:17:33.751561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.751561Z digest=sha256:255362b5d4d6d061691338f41934291e1c1463fdfc6b3d7e3dfa42276e2dc875

Observation 41b3373c-b07d-437f-b348-f43316a7eaa0 · inbound

Position: It's Time to Act on the Risk of Efficient Personalized Text Generation cites this paper.

Position: It's Time to Act on the Risk of Efficient Personalized Text Generation Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 16

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unresolved
no resolver link, observed 2026-08-08T15:07:36.510251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:07:36.510251Z digest=sha256:e2ca3f5e4532fffe4491f6bd4db2092d9d008bf4bd3a5786c91f2e3a68387cda

Observation 15dbe22f-1c0c-455c-b1f7-f06fa44e7dea · inbound

Implementing Long Text Style Transfer with LLMs through Dual-Layered Sentence and Paragraph Structure Extraction and Mapping cites this paper.

Implementing Long Text Style Transfer with LLMs through Dual-Layered Sentence and Paragraph Structure Extraction and Mapping Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:18.462263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:36:18.462263Z digest=sha256:580d29ab170022b70707d61e79a9986ffd8dc85959b04f426734f5bedd9347fa

Observation ded11a61-f327-4a83-adfa-169ac0a560ad · inbound

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models cites this paper.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 45

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no resolver link, observed 2026-08-15T21:02:03.220418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.220418Z digest=sha256:60da23c725a44a0a982753dd5ec61c6db555eb3a7e95beaa68d3cd2972a838f9

Observation 67c5a2ee-96c2-407f-ad57-1980dacca223 · inbound

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals cites this paper.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 60

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no resolver link, observed 2026-08-07T14:39:53.719189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:39:53.719189Z digest=sha256:58431327df7ea7e4cd678796445f023d58971124c9bcbc258680a9e9f73c1dae

Observation 9f21d549-e516-4433-950a-f91d37f17a19 · inbound

From Reddit to Generative AI: Evaluating Large Language Models for Anxiety Support Fine-tuned on Social Media Data cites this paper.

From Reddit to Generative AI: Evaluating Large Language Models for Anxiety Support Fine-tuned on Social Media Data Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 43

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unresolved
no resolver link, observed 2026-08-07T14:35:03.834017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:03.834017Z digest=sha256:fb2229e39d1772d981a4008d0b7b544950b733b3b20332c01c69467282407e10

Observation 68f80e06-3d45-43a9-b360-e97ce81fa804 · inbound

Aligning LLMs by Predicting Preferences from User Writing Samples cites this paper.

Aligning LLMs by Predicting Preferences from User Writing Samples Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 25

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unresolved
no resolver link, observed 2026-08-07T13:30:23.380941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.380941Z digest=sha256:1da24dbd7cd42aa099e1c6098b241cab8c269f4a8e8bc30a4c9cae4bdc2a691b

Observation d461b08c-aee2-4354-9315-d2dac31d9b72 · inbound

PersonaFeedback: A Large-scale Human-annotated Benchmark For Personalization cites this paper.

PersonaFeedback: A Large-scale Human-annotated Benchmark For Personalization Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:47.145964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:47.145964Z digest=sha256:2b178192c25c264ad34be74513161bb1bcf27577517aba7ce16a0ee49a3ec079

Observation 31b30a20-2e26-48dc-91f0-ed60fb54e150 · inbound

PREF: Reference-Free Evaluation of Personalised Text Generation in LLMs cites this paper.

PREF: Reference-Free Evaluation of Personalised Text Generation in LLMs Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T22:50:43.688327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:50:43.688327Z digest=sha256:8ca059e371c3de74c1b175724fd493a68c75fe7c7009cb00ff8b394d03980185

Observation 77ba0ca9-96ea-4499-91d6-59ede4f2901b · inbound

Explicit v.s. Implicit Memory: Exploring Multi-hop Complex Reasoning Over Personalized Information cites this paper.

Explicit v.s. Implicit Memory: Exploring Multi-hop Complex Reasoning Over Personalized Information Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 2024

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unresolved
no resolver link, observed 2026-08-15T17:23:28.227224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:23:28.227224Z digest=sha256:215d25bd5b7d93be84222b5b1a965ceb983a30fbdc1c5a5b7dc81190a5f6cc3a

Observation d23ea5ce-3efd-42ec-ae09-e853b8f68634 · inbound

Personas within Parameters: Fine-Tuning Small Language Models with Low-Rank Adapters to Mimic User Behaviors cites this paper.

Personas within Parameters: Fine-Tuning Small Language Models with Low-Rank Adapters to Mimic User Behaviors Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T19:08:30.884858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:08:30.884858Z digest=sha256:777fdae05d52b5727c477613f06ece4ff12a3ba16dbf7bd282f0c763dffc7f00

Observation 67d13759-8aa6-48be-98ac-f91c60f0ca37 · inbound

PersonaVLM: Long-Term Personalized Multimodal LLMs cites this paper.

PersonaVLM: Long-Term Personalized Multimodal LLMs Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-15T08:05:15.526364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T08:02:10.327523Z digest=sha256:572867359744ef9ff0de274bc7fd916532d13af14702ea403c2a05722ceed946

Observation 5ccc7d0a-922a-40d9-8905-9952760b9284 · inbound

JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew cites this paper.

JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 12

Resolution
malformed identifier
arxiv_id, observed 2026-05-11T12:06:02.370112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T04:12:32.790355Z digest=sha256:32cf5debf1a728aebb852b3c5daa7b7c67ca438158711d3d4319e1503870a5a2

Observation 9a6d5127-fbdd-4c9d-8324-525cfa8f3cc0 · inbound

Personal Visual Context Learning in Large Multimodal Models cites this paper.

Personal Visual Context Learning in Large Multimodal Models Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:06:37.262336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T03:42:15.402131Z digest=sha256:7746252c0c95d5468641fba58207ff9a27d2aa7efa3e01d9da6542baa8a1e094

Observation f0fc0265-f837-4e45-8b59-99d730bb4352 · inbound

Memory-Induced Tool-Drift in LLM Agents cites this paper.

Memory-Induced Tool-Drift in LLM Agents Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 35

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verified exact
arxiv_id, observed 2026-06-30T00:24:04.410780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T00:14:36.908022Z digest=sha256:454c5b2370e5e51d79f116c501af442c57b8648e9264bdb3a92a567c34ec65f6

Observation b7539515-c42f-4b27-862c-22b01501bd4d · inbound

User as Engram: Internalizing Per-User Memory as Local Parametric Edits cites this paper.

User as Engram: Internalizing Per-User Memory as Local Parametric Edits Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-04T01:09:19.445491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-26T20:37:01.382431Z digest=sha256:1f82a1e0e8233fed586ba9761d5208dfc040c6e5cbd16833a6f3bcd567eb045c

Observation 576d2e65-363b-4568-a0a0-c030a9896d8d · inbound

CoPersona: Collaborative Persona Graphs for Robust LLM Personalization cites this paper.

CoPersona: Collaborative Persona Graphs for Robust LLM Personalization Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 65

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verified exact
arxiv_id, observed 2026-07-03T18:28:48.365517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-03T18:20:53.930801Z digest=sha256:1969a2ba99b5c4b33d8861ae4bc5db9d00f30bb34aa3bc9a5242eaad895d5004

Observation cff6759d-49aa-45df-8630-b3f3a6c56f75 · inbound

Small Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters cites this paper.

Small Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 16

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no resolver link, observed 2026-08-03T11:03:01.969722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:03:01.969722Z digest=sha256:5572117759520c90ed93f27e1385cd15dcc9752328e63b25fefbc637b08fc6f4

Observation 865bf7d0-1b2b-4825-8a14-7a6db92f4ce7 · inbound

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning cites this paper.

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 8

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no resolver link, observed 2026-08-11T16:11:47.382567Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:11:47.382567Z digest=sha256:8b1876ab6ec44413d94a3c3e3addaedf1f105a26aed8d0fb8654de334ad83d87

Observation 320b4752-14ac-4892-81c5-d47968e78b6d · inbound

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning cites this paper.

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 8

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no resolver link, observed 2026-08-14T04:20:54.265392Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:20:54.265392Z digest=sha256:b5a23ba663517366af91df3e5654dd63e033ab74ce9d9d09fc4f77651fd20f25