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Paper Citation Record · LEDGER

Towards Understanding Distilled Reasoning Models: A Representational Approach

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.03730.

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

pith.paper-citation-record.v1
2503.03730 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:45:00.068336Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T05:32:20.228263Z

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 963a99e5-8b87-4347-bc6c-33ec5f7679fa · inbound

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation cites this paper.

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation Towards Understanding Distilled Reasoning Models: A Representational Approach

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:45:00.068336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:45:00.068336Z digest=sha256:1a2b94a5938edb5d1965f505a167c7f40f17f712dbac110fbe2a8f38eca46812

Observation 49d9a1d0-26a7-4f0b-87fa-0f67fd7633a6 · inbound

CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning cites this paper.

CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning Towards Understanding Distilled Reasoning Models: A Representational Approach

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T14:50:27.835115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:50:27.835115Z digest=sha256:badc6594d2ef1e253bc79d80b72d9903b8057ef13f947ac76ab9194ec4182f3c

Observation ac797b4c-261b-443b-baec-f14ac1dc1d08 · inbound

Fine-Tuning Small Reasoning Models for Quantum Field Theory cites this paper.

Fine-Tuning Small Reasoning Models for Quantum Field Theory Towards Understanding Distilled Reasoning Models: A Representational Approach

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T03:24:15.018498Z

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=2026-05-10T03:23:18.770963Z digest=sha256:34258a56fbc01e6deb83ad735aad1dfcf94bc53e807988cf952afa3c8ebac843

Observation 6ecc559f-a55a-4157-a049-0eb06d4c66b5 · inbound

fmxcoders: Factorized Masked Crosscoders for Cross-Layer Feature Discovery cites this paper.

fmxcoders: Factorized Masked Crosscoders for Cross-Layer Feature Discovery Towards Understanding Distilled Reasoning Models: A Representational Approach

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:51:24.050593Z

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=2026-05-12T04:54:41.225199Z digest=sha256:2284de5946d68eb4a3134f0977ca26566009cd818d7c63d9c87f2c6861603970

Observation 0f5a08da-90c8-4bd6-98b2-303268abb71e · inbound

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning cites this paper.

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning Towards Understanding Distilled Reasoning Models: A Representational Approach

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:32:20.229855Z

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=2026-05-13T05:27:37.521421Z digest=sha256:5bb8370dd69c6dd96f16bf4452e0c128dd540c5dc0d450305995f4cec2effc61