Paper Citation Record · LEDGER

From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2410.05459.

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

pith.paper-citation-record.v1
2410.05459 v2

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 2026-08-16T06:30:59.297886+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:39:55.101972Z

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 7dda2a9b-e9a1-410b-b2db-4868a9765058 · inbound

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation cites this paper.

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-09T17:37:40.787506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3743882-f94d-451a-bbc8-96d8964191d8 · 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 From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T05:22:33.468853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 471940bf-60e2-48b6-bc36-428bcb39696a · inbound

How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias cites this paper.

How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T04:39:55.101972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 939fe7ff-cdb3-4f8f-88fc-e807cdd348f8 · inbound

Minimalist Softmax Attention Provably Learns Constrained Boolean Functions cites this paper.

Minimalist Softmax Attention Provably Learns Constrained Boolean Functions From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:21:01.863974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c59a0ee-c65c-4fe3-8215-7a17f3099a43 · inbound

Learning Compositional Functions with Transformers from Easy-to-Hard Data cites this paper.

Learning Compositional Functions with Transformers from Easy-to-Hard Data From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:39.840714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ae8667b-f9ac-43d8-b442-f3e6c35a4cdc · inbound

Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression cites this paper.

Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T22:10:17.592712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42f0197e-30c9-46bb-a399-aea76b88e17d · inbound

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge cites this paper.

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T05:27:44.529687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f8fbc10-55d4-40ce-82d7-6c4d511cdeff · inbound

On the Emergence of Implicit Curriculum in RLVR Learning Dynamics cites this paper.

On the Emergence of Implicit Curriculum in RLVR Learning Dynamics From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T23:11:56.681936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b2affc-a800-43ae-86ad-2d78e95b882a · inbound

The Power of Power Law: Asymmetry Enables Compositional Reasoning cites this paper.

The Power of Power Law: Asymmetry Enables Compositional Reasoning From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:31:08.381738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8a1e30ca-2190-41fe-84d1-9b468517f84d · inbound

The Power of Power Law: Asymmetry Enables Compositional Reasoning cites this paper.

The Power of Power Law: Asymmetry Enables Compositional Reasoning From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-12T18:26:05.728364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe5c8a4d-2b15-42e1-a141-fe0270cbd952 · inbound

The two clocks and the innovation window: When and how generative models learn rules cites this paper.

The two clocks and the innovation window: When and how generative models learn rules From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:16:18.110627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4d011ce6-1534-47bc-9fb4-589d17a05c06 · inbound

Steered Generation via Gradient-Based Optimization on Sparse Query Features cites this paper.

Steered Generation via Gradient-Based Optimization on Sparse Query Features From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:36:40.299551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eb03379a-a679-44aa-9a4b-782d9255ef4b · inbound

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

Transformers Provably Learn to Internalize Chain-of-Thought From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:30.594670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9d47d62b-7dbe-4f2f-90bf-83035e95c9f1 · inbound

Agentic Transformers Provably Learn to Search via Reinforcement Learning cites this paper.

Agentic Transformers Provably Learn to Search via Reinforcement Learning From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T23:42:49.906343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.