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Paper Citation Record · LEDGER

BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.23918.

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

pith.paper-citation-record.v1
2410.23918 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:46:30.979284Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T12:28:16.822869Z

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 8f91ae48-9f3b-44f3-865e-55e5f2e4c193 · inbound

CURing Large Models: Compression via CUR Decomposition cites this paper.

CURing Large Models: Compression via CUR Decomposition BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T21:46:30.979284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:46:30.979284Z digest=sha256:aa1a87ee321b2339f2f845c69eb57de40c10c8c252f9b593ff354942f8272c34

Observation 01f65777-d32c-41f0-8a22-e242c9d97dfa · inbound

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets cites this paper.

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:28:16.824274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-20T12:25:39.417436Z digest=sha256:f5f306a765ad70ed09fac100e836978c5f38a731ab82fefd3b24756dbba75112