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Paper Citation Record · LEDGER

The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.01204.

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

pith.paper-citation-record.v1
2404.01204 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:56:44.133665Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T06:38:05.737789Z

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 e25b524f-8505-45fa-a843-9645bfc4b403 · inbound

Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs cites this paper.

Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T17:56:44.133665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:56:44.133665Z digest=sha256:e97ba2400d7838088f5da2de584c3b4b0a5a357d426b9bb206fab69184871aa8

Observation babcd6d3-4b1d-4a7e-901a-6eae7a490c07 · inbound

TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning cites this paper.

TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:38:05.739081Z

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.

source=pdf_text observed=2026-05-20T06:36:20.078866Z digest=sha256:b8a1affcff006f9f8f875dbdb0b2989033c883ce6f6070eccefbe080bd033b19