Paper Citation Record · LEDGER

Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1910.06611.

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

pith.paper-citation-record.v1
1910.06611 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:17:27.968681Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T18:17:00.275942Z

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 1254f68f-6df5-4bae-bec7-9842a63a1903 · inbound

DeBERTa: Decoding-enhanced BERT with Disentangled Attention cites this paper.

DeBERTa: Decoding-enhanced BERT with Disentangled Attention Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-13T04:50:53.658911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 107fa933-8637-4765-87dd-09a8ae1619ef · inbound

Scaling Laws for Autoregressive Generative Modeling cites this paper.

Scaling Laws for Autoregressive Generative Modeling Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:49:43.902143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64b6f3bf-e99d-4f20-89a8-912d25dc1e8d · inbound

Scaling Laws for Transfer cites this paper.

Scaling Laws for Transfer Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T00:58:13.328727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e3484c64-bd7a-43dd-90c6-e3582da6a019 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:22:59.445481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation aa90d2d1-841c-4d67-9d32-485a2f31573f · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 119

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T15:42:47.730272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fcddfd55-646e-4a56-8af5-cbaf7bad18c8 · inbound

Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention cites this paper.

Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:17:00.278592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bf7d0f5b-b5ea-4b20-9ba1-b6849bfa5cff · inbound

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends cites this paper.

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-10T22:17:27.968681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8d973c8-9dd5-412a-8e0a-155b2e8c053d · inbound

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions cites this paper.

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:30.168279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.