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Paper Citation Record · LEDGER

Can Language Models Learn to Skip Steps?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2411.01855.

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

pith.paper-citation-record.v1
2411.01855 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:46:21.553797Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T17:12:25.279751Z

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 d33087e5-0cc8-4b5c-ae48-36b6804f4e3a · inbound

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models cites this paper.

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models Can Language Models Learn to Skip Steps?

Reference 115

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T01:29:57.434107Z

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=2026-05-14T01:29:56.480020Z digest=sha256:186eda7e1dc567a215fd7e950e00343ef3488d29bba83dc14c996a02a282cbcc

Observation 14a1197b-3fdc-4807-8224-d611074c511a · inbound

Fast Quiet-STaR: Thinking Without Thought Tokens cites this paper.

Fast Quiet-STaR: Thinking Without Thought Tokens Can Language Models Learn to Skip Steps?

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:21.553797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:46:21.553797Z digest=sha256:6ec87d7b6e5b7184121c93ef29ee590356ba95b88bd5276986d087d3f6889cc2

Observation 1885e8a4-0ffb-4775-9ade-16d1e5750c4c · inbound

VeriThinker: Learning to Verify Makes Reasoning Model Efficient cites this paper.

VeriThinker: Learning to Verify Makes Reasoning Model Efficient Can Language Models Learn to Skip Steps?

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:42:12.976815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:12.976815Z digest=sha256:24488782ceceb283eb677a683ffc3844f9de05ee4206cca44a326f17b1840141

Observation 9f0812b9-235b-422f-b9ab-e94d32a581bd · inbound

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts cites this paper.

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts Can Language Models Learn to Skip Steps?

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:27:39.117278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:39.117278Z digest=sha256:fd7f56dad76daf17f28f45f7c82ae4960fe77f4574e6ce64915c76316ff5c1a7

Observation ca5f53be-6023-47cf-9f84-ca2e4cbf4044 · inbound

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning cites this paper.

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning Can Language Models Learn to Skip Steps?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T13:54:26.905899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:54:26.905899Z digest=sha256:0a8894f2a7935081d71fe4f081b8dd7afae0e3d681d1eb506de5593efd6c13de

Observation 9acbe5aa-4f54-4fa6-a216-c3ac9d1bc68c · inbound

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models cites this paper.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Can Language Models Learn to Skip Steps?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:43.731124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.731124Z digest=sha256:038aa946fc7daa9f93eaceb8107bafd77b03c0a7ba589137185419cbd0da5476

Observation 29cdb302-a971-4b8b-8d35-b197d55327d9 · inbound

How Far Are We from Optimal Reasoning Efficiency? cites this paper.

How Far Are We from Optimal Reasoning Efficiency? Can Language Models Learn to Skip Steps?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:36.874631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:49:36.874631Z digest=sha256:ab1cbd6517e2401fa30836ac4964c1d660a26b0a5546212c5583a2514d3d3fc8

Observation 29ea50cc-b6d1-4a6c-8b6a-4dc85ddca9ab · inbound

Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty cites this paper.

Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty Can Language Models Learn to Skip Steps?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T04:38:09.483737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:38:09.483737Z digest=sha256:836935c5281acb474b650541c4eeb98acfc104a53c147794970b00baf22c55b2

Observation 84f35551-7b7f-4572-a1a8-9b642c4b643f · inbound

PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models cites this paper.

PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models Can Language Models Learn to Skip Steps?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T04:26:29.251219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:26:29.251219Z digest=sha256:6a9d4c3646c7a2fe3611e262e8a39f766b5d6399af4d7060c8d54eaeb323f6e8

Observation 11502696-71a4-4c7c-9ffd-d832e8056088 · inbound

Assembly of Experts: Linear-time construction of the Chimera LLM variants with emergent and adaptable behaviors cites this paper.

Assembly of Experts: Linear-time construction of the Chimera LLM variants with emergent and adaptable behaviors Can Language Models Learn to Skip Steps?

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T12:05:09.511104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:05:09.511104Z digest=sha256:92a741a40ebea4537dc20b97ee3de23002e0228b44a56a000b8ab6eb97888065

Observation 234bbceb-3e6d-4242-8c54-aa356122e1df · inbound

Reconsidering Overthinking: Penalizing Internal and External Redundancy in CoT Reasoning cites this paper.

Reconsidering Overthinking: Penalizing Internal and External Redundancy in CoT Reasoning Can Language Models Learn to Skip Steps?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:37.159143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:14:37.159143Z digest=sha256:138481528a51bc68e40dfdb93ddaa6673f7a7c2436302c4e860f54c972567382

Observation a53f3548-a391-43f0-91f5-ffa096dec31c · inbound

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models cites this paper.

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models Can Language Models Learn to Skip Steps?

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:22:55.285493Z

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=2026-05-16T13:21:36.606855Z digest=sha256:b7dec4cb4368933d403eedd362d605d50cce753354c3f0ff8887cce3a1c5d805

Observation 203547ee-1968-46cd-868a-9b7ede4252e7 · inbound

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost cites this paper.

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost Can Language Models Learn to Skip Steps?

Reference 61

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:06:09.698291Z

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=2026-05-08T10:19:08.451445Z digest=sha256:8d4678dd07ef559a5a386b55422076cd6ed2d3438231ccb007164ef7149420ea

Observation 0b3f4fe0-10a5-4c84-b4c6-5e2ae7878193 · inbound

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs cites this paper.

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs Can Language Models Learn to Skip Steps?

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T17:12:25.281100Z

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=2026-06-28T17:05:48.244094Z digest=sha256:06075710610b02817a7a87bb8083334e7172a3c59640f37db96b4451aac134f5