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Paper Citation Record · LEDGER

Learning to (Learn at Test Time)

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2310.13807.

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

pith.paper-citation-record.v1
2310.13807 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:55:26.905858Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:07:45.289034Z

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 17ed59ff-04d1-481c-89a6-a587fee4706b · inbound

TextGrad: Automatic "Differentiation" via Text cites this paper.

TextGrad: Automatic "Differentiation" via Text Learning to (Learn at Test Time)

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-13T11:27:58.244785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T11:27:58.098484Z digest=sha256:90f2bca66e0744d87d31b820b7bbe214431eb624c6275f9e6f5deb69ad168747

Observation 5ec828bd-1430-4813-a2d1-4632c247fb90 · inbound

Learning to (Learn at Test Time): RNNs with Expressive Hidden States cites this paper.

Learning to (Learn at Test Time): RNNs with Expressive Hidden States Learning to (Learn at Test Time)

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:20:12.272079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T05:20:12.134340Z digest=sha256:c035994a99f954976bc93aa1b30e8fece6c55f24f68d3f2ff36db35dd0ed9e03

Observation 365d0e5f-079e-4b1c-90ca-5370345dae00 · inbound

UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models cites this paper.

UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models Learning to (Learn at Test Time)

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T20:55:26.905858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:26.905858Z digest=sha256:76de811e09e613c8efc5930b3f16d6c5f3307671d8ec1ef58c82bdf699aef05f

Observation 5dd43cf7-598d-4a59-8e54-d04d7a48a18f · inbound

SLOT: Sample-specific Language Model Optimization at Test-time cites this paper.

SLOT: Sample-specific Language Model Optimization at Test-time Learning to (Learn at Test Time)

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T20:38:16.990116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:16.990116Z digest=sha256:9a502db000721fe1e0bef49fa87029830a1310dc59b3c264087560f52f78fbc3

Observation 3b83103e-1e9f-461b-b9a5-dec1486b9aa3 · inbound

Learning to Discover at Test Time cites this paper.

Learning to Discover at Test Time Learning to (Learn at Test Time)

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-16T05:16:04.218082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T05:16:04.001700Z digest=sha256:2b44731754824cdbe62c8bbe4a7c54d896fba0e29f7c81a12af9451b1fbabc6e

Observation 465aed49-f985-4b24-9cb0-7df9be896662 · inbound

Learning to Remember, Learn, and Forget in Attention-Based Models cites this paper.

Learning to Remember, Learn, and Forget in Attention-Based Models Learning to (Learn at Test Time)

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-03T03:16:07.222688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:16:07.222688Z digest=sha256:cfdf21a5503a93a20458866b23ef10c5262fc7e81eb42c90ea446c18f6b425a1

Observation 311b67f4-b193-459b-818d-f9f1ab293636 · inbound

Preconditioned DeltaNet: Curvature-aware Sequence Modeling for Linear Recurrences cites this paper.

Preconditioned DeltaNet: Curvature-aware Sequence Modeling for Linear Recurrences Learning to (Learn at Test Time)

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:19:46.613984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-10T00:19:24.366922Z digest=sha256:18097c941078771ff96bf75ef070c966b0978adef0ce7c2e4fc9dba26f2456c8

Observation 787e484a-b38f-492a-8660-392a617c9d99 · inbound

Rethinking the State Update Gate for Long-Sequence Recurrent 3D Reconstruction cites this paper.

Rethinking the State Update Gate for Long-Sequence Recurrent 3D Reconstruction Learning to (Learn at Test Time)

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:17:45.642857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T20:13:39.983216Z digest=sha256:d9cca8d7e5aa967a40e1ea224794c2ad68a1a78540e7fed3e51b378d5b7d88fe

Observation 6a7fa037-fb98-4923-81d5-74eb588972d6 · inbound

The Power of Test-Time Training for Approximate Sampling cites this paper.

The Power of Test-Time Training for Approximate Sampling Learning to (Learn at Test Time)

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:07:45.290443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T11:07:47.543592Z digest=sha256:ff713a1d1faf93dac7fa317642436c60e727d53d6f06254ff4e3a7f775605379