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Paper Citation Record · LEDGER

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

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:08:30.884858Z

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-23T21:47:28.193374Z digest=sha256:7b53f6417afa7cad620a170b66b622a2266c21ca9b31f3378d3ad90a9c38b05f

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=sha256:7bb646e6cc229068032c8eeb47d7bee86585b7765be85cf1420a4ee30197288b

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T08:02:10.327523Z digest=sha256:86f31e3ec6e2909d8ad561329339653c7dc5c4f9729924b2720629795c8fbc3b

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T04:12:32.790355Z digest=sha256:910960702008e6d1a21954e127cbd23ce34c9a541d9eae99dee3db474f9c7ac7

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-12T03:42:15.402131Z digest=sha256:40a7281432d041d1b7437a0f4e6aa7355c0cb4dbfceecf2c8037e2087bed015f

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-30T00:14:36.908022Z digest=sha256:bd0caacf74e2fafa0de0e30905282ab221632454955a3df385c0505e2cd17093

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 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-26T20:37:01.382431Z digest=sha256:68e5c8a8edccb708a216ef22bea4be7444f27281f45f1bba095433a1b228b84e

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 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-03T18:20:53.930801Z digest=sha256:d0c91925af1c23e7ac8f93ed94ac84b8a8164d31568f1fd32e6b3ee1ba2dd16a

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=sha256:6935b0f90f86cdb7fc5f9b41b9374806860af51e47ea33c3c997db325de41895