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Paper Citation Record · LEDGER

In-Context Learning Unlocked for Diffusion Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.01115.

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

pith.paper-citation-record.v1
2305.01115 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 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:18.562919Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:57:38.414262Z

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 e3b2dbcc-47a7-4ce0-a96e-3311d0f47ade · inbound

Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models cites this paper.

Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models In-Context Learning Unlocked for Diffusion Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:18.562919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:18.562919Z digest=sha256:ddb41d61615540fe6073b9cda2585794afe9425fc9b354e2a6ab22a2eeda8f77

Observation 5e4c9d5d-226f-4985-b350-23e91a3b68ef · inbound

PairEdit: Learning Semantic Variations for Exemplar-based Image Editing cites this paper.

PairEdit: Learning Semantic Variations for Exemplar-based Image Editing In-Context Learning Unlocked for Diffusion Models

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:14.741897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:14.741897Z digest=sha256:d0949cf5aec7070dcd23548fa8344bae73f49ca9f266fa2500af62a211300ab2

Observation 90505702-a319-4bcd-bf5d-b3fca881fce2 · inbound

Delta-Adapter: Scalable Exemplar-Based Image Editing with Single-Pair Supervision cites this paper.

Delta-Adapter: Scalable Exemplar-Based Image Editing with Single-Pair Supervision In-Context Learning Unlocked for Diffusion Models

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:40:53.941343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T03:33:50.738264Z digest=sha256:2ebcf5368869d975f19fccfc0efc3076d5718b194eca7306ffa9f90cd4eb1d6b

Observation 9ed13fe4-daff-4899-a926-19dd58d8d6a6 · inbound

When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing cites this paper.

When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing In-Context Learning Unlocked for Diffusion Models

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T17:07:13.127616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T22:08:57.792229Z digest=sha256:f61a9d38e18ee5bec24e91174c755635ad60311a7c10ed79aca2bebb8d527207

Observation aac9aca4-8291-4070-9e27-f8a5817ad58f · inbound

Beyond Model Size: Probing the Gaps in Visual in-Context Learning by Training a Tiny Model cites this paper.

Beyond Model Size: Probing the Gaps in Visual in-Context Learning by Training a Tiny Model In-Context Learning Unlocked for Diffusion Models

Reference 53

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:57:38.415719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T13:31:55.497762Z digest=sha256:8c999731c4c1625d8157aa2dd5ee018a002a6f0c0597734851c8757925f6d90b