Pith. sign in

Paper Citation Record · LEDGER

VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2408.17131.

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

pith.paper-citation-record.v1
2408.17131 v1

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 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:49:45.621393Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:13:13.856063Z

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 d3963329-b9b0-4367-8c43-7d04b89c8506 · inbound

Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models cites this paper.

Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:13:13.859090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-23T17:12:18.929436Z digest=sha256:82f8a1109c6fdc9b9e22622348cdbb07f759d03892d4a68d9bb9da65ba155dcb

Observation 41f3c4d6-168d-432a-ac0a-6411fca8a3cc · inbound

Diffusion Product Quantization cites this paper.

Diffusion Product Quantization VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T17:49:45.621393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:49:45.621393Z digest=sha256:b0779beb6a4835d57a8e59a5312248bbff2cf9b690ea315dd6db9ce2f88f8b44

Observation 3b579db0-c785-4488-bb8c-436653aba2e3 · inbound

Importance-Based Token Merging for Efficient Image and Video Generation cites this paper.

Importance-Based Token Merging for Efficient Image and Video Generation VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T14:24:43.297751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:24:43.297751Z digest=sha256:adc0f637183fc0b8fe1a14e2112a6d99d1eabee24893aee530888d4499b75645

Observation 7ffc83a7-313b-4f01-9841-e2bdc6c53a12 · inbound

VQ4ALL: Efficient Neural Network Representation via a Universal Codebook cites this paper.

VQ4ALL: Efficient Neural Network Representation via a Universal Codebook VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T19:32:44.210234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:32:44.210234Z digest=sha256:b3f19bf916f2ca6f3b887757c0177eaff906d98b9ce94f76d7f6d98888bcd5b4

Observation cda3e752-a9c6-4a44-a951-e049186429a4 · inbound

1.58-bit FLUX cites this paper.

1.58-bit FLUX VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T04:39:36.466927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:39:36.466927Z digest=sha256:d0caca3fbe914071a5cd17cbddee12c91ed56a5437914f7882484125a221e6e7

Observation 045fb446-2def-445d-a8c2-440719d9aee3 · inbound

Importance-Aware OBS Pruning for Diffusion Models cites this paper.

Importance-Aware OBS Pruning for Diffusion Models VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-01T10:59:55.367167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:59:55.367167Z digest=sha256:9fa8ebece78f9d9983b6eb1e89dedbd15ea346edea23eb9b4eee66e2149b05b1