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Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 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 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:07:36.510251Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T21:47:28.193374Z digest=sha256:9bff42a7587202b458c417fe157e4d727bd3e077f69381b7b32a91e6d5c4d62b

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

Resolution
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=sha256:86398f66169ef261661cbe4e45d38b690f22df21e05cf53c6578b0a1eb30f746

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

Resolution
unresolved
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=sha256:51154018cadabea28a18110ba168b2aa3fed0c68368ce42b5c9e18bb7007428c

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

Resolution
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:b270a5ae9763a0b63992ae229b77cb7ee9b9cbd365b78a0e34a26ac827d733ff

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

Resolution
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=sha256:4c3e47ad16c724265378ed76ecbaf1a628dd1875c8b9b0394076656ea117bac7

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=sha256:815d0b92010a9702ce6196f48d3dc38564627da24da750d1a614523ac4521972

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=sha256:37a38e8c3f849b8694cfa2f2d872c20a9349ed82c3638268e5375fd40cc070cb

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=sha256:8443d90d5042c1664d7759c55671281040a35c2fe58431a956d66b0b4e0ae68c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T08:02:10.327523Z digest=sha256:81eb97cb286de4ea9c4ef2bbb81bae7722e97fe68a8410ffe7e3659f818e9b32

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T04:12:32.790355Z digest=sha256:4261862f9db6bf7648e1c510e8e28a6e4eace9990d9731d2f463bec0819b7429

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:42:15.402131Z digest=sha256:917656e5b70cba1137e09c9359f522215005c1772c40c26f4db2279fb1790e1a

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T00:14:36.908022Z digest=sha256:a0b57511a7065abdbab1dc6dda7b57df92db40b6685df3551f741a0ea3908acd

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T20:37:01.382431Z digest=sha256:e93c1fa47162802254566ae137f1e3c36d2084de1e17a041fcf663930fad071e

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T18:20:53.930801Z digest=sha256:cf5df7094b9d90d62035adaf1e33935ce9c4f1ab7d514901d1cce55261576c08

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

Resolution
unresolved
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:d1b76caf749fad70a33eed1cad1036cda4e6caa3332d1f016bbdf8349b56c5fe