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Paper Citation Record · LEDGER

EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.04585.

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

pith.paper-citation-record.v1
2401.04585 v3

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 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:01:02.347514Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:31:13.787076Z

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 3c3ba1c7-5b42-4c3c-a15f-2dfcea2a83e2 · inbound

Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness cites this paper.

Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:31:13.790152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T07:31:09.035118Z digest=sha256:2ef1c763513483d815d47c3d8d81243b6e9ac2284fc60ee7ca41f58c6496a7fd

Observation 92329924-9567-4178-8ac4-088778ab041e · inbound

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation cites this paper.

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-12T09:35:12.908124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T09:35:12.908124Z digest=sha256:24f634852638862dc11ecd931b46773f653e481b28ec9ebcb96af14adcec4c98

Observation db527897-00cc-486b-b7b9-9cf4e8c7a906 · inbound

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation cites this paper.

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-14T16:53:34.398685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T16:53:34.398685Z digest=sha256:5607df40c4b5e4292dc8071b5c789a479f23f27ec90a4784fdf3b037d691fdff

Observation 0895b90a-862d-41b8-b722-46636ff5e7b3 · inbound

Quantizing Recursive Reasoning Models cites this paper.

Quantizing Recursive Reasoning Models EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T10:01:02.347514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T10:01:02.347514Z digest=sha256:b1a9407b9c5484e22ac0e7fbf1356b74f50ad80be683ad7e13ce4e31a573a801

Observation 7fd951b1-ef69-412a-96ed-c3e96a48b3e9 · inbound

Examining the Efficacy of Graph Neural Network Message-Passing in Regression Contexts cites this paper.

Examining the Efficacy of Graph Neural Network Message-Passing in Regression Contexts EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models

Reference 257

Resolution
unresolved
no resolver link, observed 2026-08-01T16:42:32.657990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T16:42:32.657990Z digest=sha256:9905888c32bf29c415b5b989e7898c8e34c2daa994dea2ae6822121f2a5f662f