Paper Citation Record · LEDGER

Contextual Position Encoding: Learning to Count What's Important

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2405.18719.

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

pith.paper-citation-record.v1
2405.18719 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:30:11.092718Z

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

3
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 8fe7196a-2244-4919-948e-23ffe2d7c2cc · inbound

Precise Length Control in Large Language Models cites this paper.

Precise Length Control in Large Language Models Contextual Position Encoding: Learning to Count What's Important

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T14:30:11.092718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 666e10d4-921f-4538-bf0f-dac7a3c594f9 · inbound

Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding cites this paper.

Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding Contextual Position Encoding: Learning to Count What's Important

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:44.801031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ba504fe-728d-40fd-8a7d-1db0f76bff5d · inbound

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data cites this paper.

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data Contextual Position Encoding: Learning to Count What's Important

Reference 187

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:35:02.177667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 74ec3da2-2372-435f-abca-c679708f39b8 · inbound

A Contextual-Aware Position Encoding for Sequential Recommendation cites this paper.

A Contextual-Aware Position Encoding for Sequential Recommendation Contextual Position Encoding: Learning to Count What's Important

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T22:56:55.667281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 723c52f5-ffcc-491a-8f30-bc2fb20c0fbf · inbound

Sample Complexity and Representation Ability of Test-time Scaling Paradigms cites this paper.

Sample Complexity and Representation Ability of Test-time Scaling Paradigms Contextual Position Encoding: Learning to Count What's Important

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:35:33.813693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0210458f-18aa-4a5f-afe7-dc7ce4437b7b · inbound

Latent Multi-Head Attention for Small Language Models cites this paper.

Latent Multi-Head Attention for Small Language Models Contextual Position Encoding: Learning to Count What's Important

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:07.482951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ca71b20-706f-4a85-a497-7f6496e1cb11 · inbound

HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models cites this paper.

HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models Contextual Position Encoding: Learning to Count What's Important

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T05:36:53.380335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38119b0b-e579-46c4-8659-be7f48197928 · inbound

Group Representational Position Encoding cites this paper.

Group Representational Position Encoding Contextual Position Encoding: Learning to Count What's Important

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:08:43.762670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 20a862ee-16be-45eb-8d83-5f3304c5e473 · inbound

Dual Triangle Attention: Effective Bidirectional Attention Without Positional Embeddings cites this paper.

Dual Triangle Attention: Effective Bidirectional Attention Without Positional Embeddings Contextual Position Encoding: Learning to Count What's Important

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T21:20:51.877914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bd9e3a89-5a5c-4d6a-91de-e68dbff3f2f5 · inbound

Hypothesis generation and updating in large language models cites this paper.

Hypothesis generation and updating in large language models Contextual Position Encoding: Learning to Count What's Important

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-08T21:14:12.639564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a4b91b6c-4f1e-496b-9b3d-cc275594ff55 · inbound

Give it Space! Explicit Disentangling of Positional and Semantic Representations in Encoders cites this paper.

Give it Space! Explicit Disentangling of Positional and Semantic Representations in Encoders Contextual Position Encoding: Learning to Count What's Important

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-29T07:33:13.050739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e3736da0-d508-4182-964d-a81e8e3f08e5 · inbound

Addressable Memory for Video World Models cites this paper.

Addressable Memory for Video World Models Contextual Position Encoding: Learning to Count What's Important

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T05:06:51.778667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.