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Paper Citation Record · LEDGER

LoCoCo: Dropping In Convolutions for Long Context Compression

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.05317.

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

pith.paper-citation-record.v1
2406.05317 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:34.119273Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:36:59.428659Z

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 7a14e433-d084-41a8-b1a7-a3f68645201e · inbound

Kinetics: Rethinking Test-Time Scaling Laws cites this paper.

Kinetics: Rethinking Test-Time Scaling Laws LoCoCo: Dropping In Convolutions for Long Context Compression

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:34.119273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:30:34.119273Z digest=sha256:419674665a385046808d6d8426cb03848aaa28c837dac6bb0cdf5067a0ffa31d

Observation 096969b8-73e4-4bfd-8f4d-7f5d8ce55915 · inbound

FAEDKV: Infinite-Window Fourier Transform for Unbiased KV Cache Compression cites this paper.

FAEDKV: Infinite-Window Fourier Transform for Unbiased KV Cache Compression LoCoCo: Dropping In Convolutions for Long Context Compression

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T14:00:42.890892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:00:42.890892Z digest=sha256:f7d5e93c440400bff7ea40fb03a6bd2f61ea0798e298c9f2ed2663a0b892cbcd

Observation 498ff9d2-29c2-4a7e-932d-79153c0b43fb · inbound

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression cites this paper.

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression LoCoCo: Dropping In Convolutions for Long Context Compression

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-22T05:11:06.206532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T05:10:53.133346Z digest=sha256:a410fc1f179c82e7cbcaaba81edc6ea4d36bbc72bf63946f52b839a4a74e913c

Observation 72687daf-13af-4362-8799-b3dd725680aa · inbound

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression cites this paper.

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression LoCoCo: Dropping In Convolutions for Long Context Compression

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-30T17:34:57.876686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T17:28:08.750049Z digest=sha256:9417f9f1e45533679ec576b065839783d721a20d46c7f5012f3533f287233152

Observation df830d6e-fdba-4269-9f77-91dc01f60442 · inbound

Vortex: Efficient and Programmable Sparse Attention Serving for AI Agents cites this paper.

Vortex: Efficient and Programmable Sparse Attention Serving for AI Agents LoCoCo: Dropping In Convolutions for Long Context Compression

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:36:59.430639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T01:07:14.691347Z digest=sha256:a78a89fe679031222d92285c8fa43d359773258373520744069dfaa8ad1ac964