Paper Citation Record · LEDGER

From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2503.05919.

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

pith.paper-citation-record.v1
2503.05919 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:05:45.250462Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:16:16.108616Z

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 2dcc3f8c-7f3e-47c9-b762-910a6871fae3 · inbound

Learning Facts at Scale with Active Reading cites this paper.

Learning Facts at Scale with Active Reading From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.250462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1e6c13a-e017-4d50-9018-57aeceb9ee9e · inbound

Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs cites this paper.

Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-18T07:22:27.812023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 90a0a749-7d2c-41bf-aa01-234c66dd0da1 · inbound

Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs cites this paper.

Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T10:36:29.488490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af0b303b-3b1f-4437-a74a-9fddecf01524 · inbound

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control cites this paper.

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:39:05.913396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 40d5d819-363f-4b96-8d8b-50a1e62aea77 · inbound

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control cites this paper.

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T20:25:23.553609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb420138-8446-440f-8778-8c2bdfd44173 · inbound

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 100

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:15:59.002290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d3deb36f-4617-4ed6-8261-df9252224865 · inbound

ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities? cites this paper.

ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities? From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:16:16.110374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.