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Paper Citation Record · LEDGER

An Analysis for Reasoning Bias of Language Models with Small Initialization

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.04375.

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

pith.paper-citation-record.v1
2502.04375 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:01:15.054309Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T20:05:04.830513Z

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 66fefe0f-4f93-47e8-9afe-9276c46157ab · inbound

An overview of condensation phenomenon in deep learning cites this paper.

An overview of condensation phenomenon in deep learning An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-22T20:05:04.833173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T20:02:41.105786Z digest=sha256:0f483a7c3661f78e5a9928d7fe3bb7cd750159313f38aa26d83372e6267ecb9f

Observation b8fc0767-8d84-497a-abfa-5756056ee175 · inbound

Scalable Complexity Control Facilitates Reasoning Ability of LLMs cites this paper.

Scalable Complexity Control Facilitates Reasoning Ability of LLMs An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:15.054309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:15.054309Z digest=sha256:1407a9af2df57101b49764f7b9f1f7a4065e52fce1ac59907ec9247b2c4be31c

Observation 6ec5b63b-4bbc-4e57-864d-1447d941c7f6 · inbound

Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge cites this paper.

Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T13:54:18.723775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T13:54:18.723775Z digest=sha256:8906e414b6585b7ce3673666ae5f806cfc3502215193e4c97d69638b46b5e9eb

Observation a616f226-79c2-4b59-a397-8de0f7fbb763 · inbound

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability cites this paper.

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-16T11:20:52.679420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T11:20:33.400885Z digest=sha256:bc80eb0f254d16d88ebc13fe3c1e2daf91bf21b648a66ee77100c8f85c720d9d

Observation 1c17a3da-46b0-4515-aaf6-d2123e7139f9 · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-15T18:10:13.250276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T18:09:54.899039Z digest=sha256:91ffbb3fb3bbce6a4ccf3241ebac14c9a5148393a55a7972e13dd6cb0876dd95

Observation 978df83f-d197-48a9-84d2-e4b6899c320e · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T19:49:44.634914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:49:44.634914Z digest=sha256:48058852f93778e337918e27eef9d0ce16d2c6b23742c124192051bd4c743447