Paper Citation Record · LEDGER

Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2101.00234.

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

pith.paper-citation-record.v1
2101.00234 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 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:59:48.316556Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T03:37:35.911449Z

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 9bcbf74b-1ddb-47e3-ad53-9f5b398d549c · inbound

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing cites this paper.

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:59:48.316556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1670984e-e07c-45cc-b215-65dd36744b62 · inbound

BWTA: Accurate and Efficient Binarized Transformer by Algorithm-Hardware Co-design cites this paper.

BWTA: Accurate and Efficient Binarized Transformer by Algorithm-Hardware Co-design Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:28:02.199807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 93a90e85-af2f-4dd0-9ce8-3869aa3b0cb2 · inbound

SMolLM: Small Language Models Learn Small Molecular Grammar cites this paper.

SMolLM: Small Language Models Learn Small Molecular Grammar Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:01:17.304352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e1ac644-a97f-4ff1-b9f8-091a05489080 · inbound

Do Transformers Need Three Projections? Systematic Study of QKV Variants cites this paper.

Do Transformers Need Three Projections? Systematic Study of QKV Variants Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:36:17.338984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 931bffe4-b07b-4d02-a755-92db7ce523c3 · inbound

Rethinking Depth: A study of the Recursive-Transformer for Speech Recognition cites this paper.

Rethinking Depth: A study of the Recursive-Transformer for Speech Recognition Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-03T03:37:35.913464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7f1138dc-a69e-42a4-a12a-62a25f3bcaa2 · inbound

Mobius Learning: Cyclic Depth Folding in Transformers cites this paper.

Mobius Learning: Cyclic Depth Folding in Transformers Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T16:53:42.881763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.