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Paper Citation Record · LEDGER

A Formal Framework for Understanding Length Generalization in Transformers

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.02140.

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

pith.paper-citation-record.v1
2410.02140 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:02:56.682003Z

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 8c7f0f33-a480-4e8a-94c1-5a1879bc72fb · inbound

Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law A Formal Framework for Understanding Length Generalization in Transformers

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-03T14:02:56.682003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:02:56.682003Z digest=sha256:f859a95a2b190cb0352a8691862b3ba0305268c227c40ce7cbe21b5962915c63

Observation 7eccc9a2-af27-41e9-a3d6-c577aab4c10c · inbound

On the Spatiotemporal Dynamics of Generalization in Neural Networks cites this paper.

On the Spatiotemporal Dynamics of Generalization in Neural Networks A Formal Framework for Understanding Length Generalization in Transformers

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:00:46.839589Z

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=2026-05-16T08:59:44.016444Z digest=sha256:fd8307f64fcf9b327ef96a57bf043704452944ce9ed73b2661e6b1ac41bc1fd4

Observation c120a8e6-4d07-4765-8a9a-712afbdd8607 · inbound

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication cites this paper.

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication A Formal Framework for Understanding Length Generalization in Transformers

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:07:57.571562Z

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=2026-05-14T21:07:37.032208Z digest=sha256:59f912908c1f922df5a029e6f2bc797e97aed27aae57cc3a66d4af198653944d

Observation 1a39b18f-89d1-4024-a2d8-682896487fae · inbound

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

Agentic Transformers Provably Learn to Search via Reinforcement Learning A Formal Framework for Understanding Length Generalization in Transformers

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:42:49.930399Z

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=2026-06-28T23:26:28.158991Z digest=sha256:d9bd8709233ea6d771fbb66807611eb474c275c00761f6d829245c0e3c2b8814

Observation 24211108-9caf-4f93-bfa0-0d4cb80db009 · inbound

From Expressivity to Sample Complexity: Narrow Teachers for Transformers via C-RASP cites this paper.

From Expressivity to Sample Complexity: Narrow Teachers for Transformers via C-RASP A Formal Framework for Understanding Length Generalization in Transformers

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-14T03:23:31.727605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T03:23:31.727605Z digest=sha256:a8f8a396349444134b1cefdb973eae516bf5276dcc12ba848e8c46c4864530eb

Observation b1f74490-9223-40c8-acb6-f91918ced5a5 · inbound

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary cites this paper.

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary A Formal Framework for Understanding Length Generalization in Transformers

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T07:20:39.812148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T07:20:39.812148Z digest=sha256:610a20fdea334514ef6dcc8686bc54894ea180d14582f6da65c92ff9c8452757