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Paper Citation Record · LEDGER

Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2502.20339.

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

pith.paper-citation-record.v1
2502.20339 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 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:58:36.285389Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a9ea3fe3-3c78-41a9-84cb-fcfdc12c99e8 · inbound

Scaling over Scaling: Exploring Test-Time Scaling Plateau in Large Reasoning Models cites this paper.

Scaling over Scaling: Exploring Test-Time Scaling Plateau in Large Reasoning Models Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:58:36.285389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:58:36.285389Z digest=sha256:ee0b85b79fd819b69622c46af7156724d514f9f600c77f27697c74c01dd37b49

Observation 5a899b0a-ddf2-4b4d-925a-6af2c1f3fde8 · inbound

Kinetics: Rethinking Test-Time Scaling Laws cites this paper.

Kinetics: Rethinking Test-Time Scaling Laws Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:34.355793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:30:34.355793Z digest=sha256:df39bff9d1722d7733d15224e080cb125cd887e0e1f9bd89331265e38097bca7

Observation e8672c6f-2656-4a01-b1a5-7f99b419da35 · inbound

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 144

Resolution
unresolved
no resolver link, observed 2026-08-06T17:54:17.548405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:17.548405Z digest=sha256:db873fcb64ac1aa294e5b69f40aef7ab7c3180c3bd64f632e11cb5292bd09a09

Observation c767df98-3354-47c3-8098-fc29674c8615 · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 106

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:32:46.647169Z

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=arxiv_source observed=2026-06-28T23:29:02.457697Z digest=sha256:0151ee2ad7e0a87cef6d75d447dd784ffc65e33506c5e54883b820b6b204c250

Observation e8094d3a-8494-4fa8-a698-fc0581b6540a · inbound

Morphing into Hybrid Attention Models cites this paper.

Morphing into Hybrid Attention Models Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:44:28.077719Z

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=2026-06-30T05:56:51.447893Z digest=sha256:c839c35411d20fe917b5781e5f91e59c154101bf38eb6207f90edc01e102d2ed

Observation af096754-c3b6-4507-be41-b5f893d81905 · inbound

Raven: High-Recall Sequence Modeling with Sparse Memory Routing cites this paper.

Raven: High-Recall Sequence Modeling with Sparse Memory Routing Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T02:44:01.671659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:44:01.671659Z digest=sha256:8e000792218a2cfb0d041628f56653a608e241da526797f24a105a701e891e28

Observation 144c04ea-677e-4c8d-b995-b7a531e3ebed · inbound

Evaluating Theory of Mind in Reasoning Models: Robustness over Reasoning cites this paper.

Evaluating Theory of Mind in Reasoning Models: Robustness over Reasoning Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T19:57:57.120102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:57:57.120102Z digest=sha256:b2a92ab1e7b984e08cbeb6ba21c5e0b3e497ce4433ec723fc88e129190f95b8e