Paper Citation Record · LEDGER

Transformer-based Image Compression

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2111.06707.

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

pith.paper-citation-record.v1
2111.06707 v1

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 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:55.122972Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:39:38.960237Z

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 1c9a0532-3550-4e71-ac41-4885455bbf60 · inbound

Large Language Models as Computable Approximations to Solomonoff Induction cites this paper.

Large Language Models as Computable Approximations to Solomonoff Induction Transformer-based Image Compression

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T15:16:55.122972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 277f82f8-41c4-476e-bafd-000783d9a410 · inbound

What and Where to Adapt: Structure-Semantics Co-Tuning for Machine Vision Compression via Synergistic Adapters cites this paper.

What and Where to Adapt: Structure-Semantics Co-Tuning for Machine Vision Compression via Synergistic Adapters Transformer-based Image Compression

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:31:02.424308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b57d53d7-2c2d-40b2-a04f-c9006bbe95c0 · inbound

SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression cites this paper.

SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression Transformer-based Image Compression

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:01:05.412720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 562e96ff-a672-485d-8339-23dd0cc4e770 · inbound

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts cites this paper.

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts Transformer-based Image Compression

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T07:39:38.962375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.