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Paper Citation Record · LEDGER

Guiding Language Model Reasoning with Planning Tokens

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2310.05707.

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

pith.paper-citation-record.v1
2310.05707 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:22:33.453157Z

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

2
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 e5a515b5-0b2d-4516-954e-cddbff8b0cdf · inbound

Training Large Language Models to Reason in a Continuous Latent Space cites this paper.

Training Large Language Models to Reason in a Continuous Latent Space Guiding Language Model Reasoning with Planning Tokens

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T10:29:05.849827Z

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=2026-05-11T10:29:05.384381Z digest=sha256:f9d2cb80526176f11444a9afb0d762fba5a0fdf36310152df812c95c124a7190

Observation 38089244-ea72-4893-8b3c-42db39940a37 · inbound

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning cites this paper.

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning Guiding Language Model Reasoning with Planning Tokens

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T05:22:33.453157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T05:22:33.453157Z digest=sha256:537e4f3bdf5240425ee2a6993fe1bf068fe8c0eace5d7662bdee0e38bb0bf8a4

Observation f65a2bf2-cc6e-46bf-9202-44be265fa7bf · inbound

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space cites this paper.

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space Guiding Language Model Reasoning with Planning Tokens

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:15:43.552964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:15:43.552964Z digest=sha256:74cb3d971f358cdb6ed067f3cbc2b2d4cc0b7e7408012a2a5280dd7fa0bb3217

Observation b500edd9-13d3-4901-9830-6f809c7389e1 · inbound

$PD^3F$: A Pluggable and Dynamic DoS-Defense Framework Against Resource Consumption Attacks Targeting Large Language Models cites this paper.

$PD^3F$: A Pluggable and Dynamic DoS-Defense Framework Against Resource Consumption Attacks Targeting Large Language Models Guiding Language Model Reasoning with Planning Tokens

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:04.795366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:04.795366Z digest=sha256:51a7ca2d13b68044e8c14a812f20da27c7e617baec8ca863df0acf737a47c96b

Observation 401bc4f2-6c3d-4e3f-a821-2c2e6a934102 · inbound

Learning a Continue-Thinking Token for Enhanced Test-Time Scaling cites this paper.

Learning a Continue-Thinking Token for Enhanced Test-Time Scaling Guiding Language Model Reasoning with Planning Tokens

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:12:14.864608Z

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=2026-05-19T09:09:08.270936Z digest=sha256:ab06e1bb1b1ad0853a18a9cfcf82c541536db7039ef88d0e5f4995345a77993e

Observation 3cdfb25a-4cc8-4801-a06b-3bc6d1d4f1f5 · 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 Guiding Language Model Reasoning with Planning Tokens

Reference 194

Resolution
unresolved
no resolver link, observed 2026-08-06T17:54:17.814129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:17.814129Z digest=sha256:74b3f0929cf1076eb2708279802a4f492e4e43220a19bc09b87b788080f3bdce

Observation be2cd549-c65c-4cff-b026-45dcb6f5b4e5 · inbound

SeLaR: Selective Latent Reasoning in Large Language Models cites this paper.

SeLaR: Selective Latent Reasoning in Large Language Models Guiding Language Model Reasoning with Planning Tokens

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:35:49.747021Z

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=2026-05-10T18:27:36.132030Z digest=sha256:9085506d7fa7791cf39e9404fd6175df1111df26c8c820b4f60443025046f857

Observation 47a20374-0185-4c3d-aa3d-1e7e3fbf435a · inbound

PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models cites this paper.

PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models Guiding Language Model Reasoning with Planning Tokens

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:18:15.715391Z

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=2026-05-14T23:17:29.025222Z digest=sha256:3036b574ab94c1d042370f62ad4abfb9e19cb04813afb15bdd2da886bc5f7ca6

Observation 55384790-8d31-4b25-ba9a-df7aff8f7213 · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering Guiding Language Model Reasoning with Planning Tokens

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-09T23:54:45.119008Z

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=2026-05-09T23:51:47.724033Z digest=sha256:d5ee7c8205f3ea7bf8947aff1324245d3d87dc5119137b739c38f87e1f2dadc1

Observation 0208830d-0b7f-4d07-838e-322dd599e404 · inbound

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning Guiding Language Model Reasoning with Planning Tokens

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:41:24.449995Z

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=2026-05-12T00:51:40.815981Z digest=sha256:d799ca5d48896fc1a82a187464eb4a0b6c42c89a9dc7fb8164a071cd8c4df7a9

Observation 738ab6bb-f6bb-4b9a-86a5-ef9b3cbb65c0 · inbound

Transformers Provably Learn to Internalize Chain-of-Thought cites this paper.

Transformers Provably Learn to Internalize Chain-of-Thought Guiding Language Model Reasoning with Planning Tokens

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:33:30.599525Z

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=2026-06-29T14:29:10.010212Z digest=sha256:6d6c034663d4071c48f554768f4ba679e1cf400d14f95bd10aa94e29802fd43c

Observation 6bb1c112-41d1-4194-8ee6-747af6f91f8a · inbound

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning cites this paper.

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning Guiding Language Model Reasoning with Planning Tokens

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:56:59.380788Z

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=2026-07-02T13:46:59.407102Z digest=sha256:57c4cc0ad4025d07a128fa57fa8b845325816c93177b8128b2215550f00108ce

Observation 89083d53-ffc7-4621-b44a-7c08f3a57b1d · inbound

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning cites this paper.

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning Guiding Language Model Reasoning with Planning Tokens

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-02T09:18:44.755088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:18:44.755088Z digest=sha256:0d05127da80b892ab44dac4b52d659e241ac54db9e516a55f84f7b8029f6292c