Paper Citation Record · LEDGER

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.02653.

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

pith.paper-citation-record.v1
1910.02653 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:52:15.447984Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:27:22.461276Z

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 0441f781-707d-4e35-833c-f37058ba8d86 · inbound

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models cites this paper.

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:24:35.870495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e641ad89-2d96-406c-9d69-99ce535abf8c · inbound

DaCe AD: Unifying High-Performance Automatic Differentiation for Machine Learning and Scientific Computing cites this paper.

DaCe AD: Unifying High-Performance Automatic Differentiation for Machine Learning and Scientific Computing Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T11:52:15.447984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1687844b-b982-4332-b8cf-1d69487750ea · inbound

Have I Solved This Before? Retrieving Similar Segmentation Problems for Evolutionary Learning cites this paper.

Have I Solved This Before? Retrieving Similar Segmentation Problems for Evolutionary Learning Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:27:22.462948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 63342bb5-4f5d-4604-8bd8-8959d02b57a2 · inbound

Xema: Efficient Diffusion Serving through Fine-Grained Memory Management and Auto-Configuration cites this paper.

Xema: Efficient Diffusion Serving through Fine-Grained Memory Management and Auto-Configuration Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T06:49:04.349040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.