Pith. sign in

Paper Citation Record · LEDGER

Compositional Visual Generation with Composable Diffusion Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2206.01714.

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

pith.paper-citation-record.v1
2206.01714 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:04:47.195759Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 76748ce7-52d9-4aab-92fb-23365911c1ce · inbound

Aligning Text-to-Image Models using Human Feedback cites this paper.

Aligning Text-to-Image Models using Human Feedback Compositional Visual Generation with Composable Diffusion Models

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:39:15.492635Z

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=2026-05-14T20:39:15.388881Z digest=sha256:cbb3064c9175338dd6882cfd551ab92a5ca9d801bb69bbc6a5edfd9733fc3dc1

Observation 20285424-595b-4a5a-8b1c-c6be35c7bfea · inbound

Training Diffusion Models with Reinforcement Learning cites this paper.

Training Diffusion Models with Reinforcement Learning Compositional Visual Generation with Composable Diffusion Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:16:31.271091Z

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=2026-05-11T20:16:30.840184Z digest=sha256:ca73917ecd7b5df53c2dd04bc139d24046ef7252880476a83a302e9fd7f7b520

Observation 6c7e9be2-9fce-43c6-a02c-590f692fb86a · inbound

Improving Factuality and Reasoning in Language Models through Multiagent Debate cites this paper.

Improving Factuality and Reasoning in Language Models through Multiagent Debate Compositional Visual Generation with Composable Diffusion Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:01:45.190561Z

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=2026-05-12T03:01:45.164412Z digest=sha256:8a16e3b514993b576cf7cd0b5da624529df7e9710944c61edc00c09419032144

Observation 988ee760-8aa7-465c-aff5-a9cec1cfe7bf · inbound

Learning Interactive Real-World Simulators cites this paper.

Learning Interactive Real-World Simulators Compositional Visual Generation with Composable Diffusion Models

Reference 187

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T02:15:18.677830Z

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=arxiv_source observed=2026-05-16T02:15:18.265190Z digest=sha256:6dab6deac54969a61479ff40cbe4f12324e48a2490b6472d6d3af249dcc2f638

Observation 2987bede-615a-42d4-961b-8fbf7cedf034 · inbound

VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models cites this paper.

VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models Compositional Visual Generation with Composable Diffusion Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-09T12:04:47.195759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:04:47.195759Z digest=sha256:9b67181091dbe0b0d51be326728bc8fcfe285bcbfb8a77aa69a73e4d9fef915b

Observation 3b9d7ced-726c-4517-a0eb-5e95ce7da35f · inbound

Compositional Scene Understanding through Inverse Generative Modeling cites this paper.

Compositional Scene Understanding through Inverse Generative Modeling Compositional Visual Generation with Composable Diffusion Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:31:07.277041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:31:07.277041Z digest=sha256:4bb464f5dc2554fa6c97d6708ab4d63babea34a2b8d36984f9ac3240881f9e3b

Observation 0c9d4880-0781-4eaa-a364-e680ac9a6c13 · inbound

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models cites this paper.

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models Compositional Visual Generation with Composable Diffusion Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T21:48:54.880447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:48:54.880447Z digest=sha256:0260b7d66826bb014fc5a7fe8be9968704e76b72fdc89c7151878a5697118de0

Observation fb28e6c0-6c50-4872-90f9-ec3166c33fd8 · inbound

Beyond Sliders: Mastering the Art of Diffusion-based Image Manipulation cites this paper.

Beyond Sliders: Mastering the Art of Diffusion-based Image Manipulation Compositional Visual Generation with Composable Diffusion Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T16:57:08.848047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:57:08.848047Z digest=sha256:98d79bab7d6f60461527868c2c21367e7c197f86109fbea1b1761cffa999640e

Observation e0340d81-1283-41fc-8355-30a6d8d7f256 · inbound

Multi-Modal Manipulation via Multi-Modal Policy Consensus cites this paper.

Multi-Modal Manipulation via Multi-Modal Policy Consensus Compositional Visual Generation with Composable Diffusion Models

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:51:20.231334Z

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=2026-05-18T11:50:20.766891Z digest=sha256:e86e9fab569ddfd01946fb32e952b7e7b7c8b8ca34ba4933c24bdf6e3c09b4bb

Observation b09319ea-3d88-4b3c-bae5-dc9deeba2415 · inbound

A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios cites this paper.

A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios Compositional Visual Generation with Composable Diffusion Models

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-16T18:58:18.268127Z

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=2026-05-16T18:57:06.742017Z digest=sha256:9aa1fdb805827c787f916b234ef3807af1fd9e6b42b8f23ed84a57ae7c1a6321

Observation ac160add-e9ac-48df-a32e-94df98375934 · inbound

$Z^2$-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models cites this paper.

$Z^2$-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models Compositional Visual Generation with Composable Diffusion Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:06:15.260949Z

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=2026-05-08T06:41:04.597012Z digest=sha256:604657a06dc96d80dab0470ee0a95923d22daf8504ca5b1a700c98e4e763d251

Observation c8172ef5-784f-410d-8c6b-d6f2046383bd · inbound

Stylistic Attribute Control in Latent Diffusion Models cites this paper.

Stylistic Attribute Control in Latent Diffusion Models Compositional Visual Generation with Composable Diffusion Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-08T18:44:00.014822Z

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=arxiv_source observed=2026-05-08T18:43:21.423012Z digest=sha256:ee63520307de22a0401ea4b2dcf625560f7be03de6eb88a8c731d070c8183cd3

Observation 9db1815e-c8e7-4663-b52e-bdc067770ac4 · inbound

Proposal-Conditioned Latent Diffusion for Closed-Loop Traffic Scenario Generation cites this paper.

Proposal-Conditioned Latent Diffusion for Closed-Loop Traffic Scenario Generation Compositional Visual Generation with Composable Diffusion Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:39:50.143248Z

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=2026-06-26T05:07:04.586974Z digest=sha256:de94c1b8354de34a46c131d910687a627221f27c6bf9ee955bb266f27fe8d7b7