Paper Citation Record · LEDGER

Improving Compositional Generation with Diffusion Models Using Lift Scores

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2505.13740.

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

pith.paper-citation-record.v1
2505.13740 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:17:31.705030Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T08:36:41.387164Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:39:45.711612Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy7
unresolved16
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cee22678-f023-467c-9ec5-9be706965920 · outbound

This paper cites K., Wang, Y .-X., and Hebert, M.

Improving Compositional Generation with Diffusion Models Using Lift Scores K., Wang, Y .-X., and Hebert, M

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.224532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fb9a7308-cae8-4f8c-898d-1e5dc31e2534 · outbound

This paper cites Here, we provide another perspective to interpret the numbers.

Improving Compositional Generation with Diffusion Models Using Lift Scores Here, we provide another perspective to interpret the numbers

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T20:17:32.029387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 987e789b-f374-45a3-a070-027243e4bb4e · outbound

This paper cites Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis.

Improving Compositional Generation with Diffusion Models Using Lift Scores Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.575605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f14bb1f6-8ca9-4b59-80df-7b12ffb5ee87 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Improving Compositional Generation with Diffusion Models Using Lift Scores Classifier-Free Diffusion Guidance

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.581671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d80490c9-c30f-4173-9a13-36fbdb20126b · outbound

This paper cites Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models.

Improving Compositional Generation with Diffusion Models Using Lift Scores Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.591863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00ab64f-3dad-42b2-9ff5-44320883d4c1 · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

Improving Compositional Generation with Diffusion Models Using Lift Scores Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.603390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aefcd7e0-7481-486b-953c-6bc394ca8177 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Improving Compositional Generation with Diffusion Models Using Lift Scores SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.616857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39c3cdaf-6e1a-4be5-8771-73df91e944df · outbound

This paper cites Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization.

Improving Compositional Generation with Diffusion Models Using Lift Scores Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.623972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e7798ee-51a5-4523-b0d9-ef5bc9ece807 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Improving Compositional Generation with Diffusion Models Using Lift Scores SAM 2: Segment Anything in Images and Videos

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.631746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f63e9fc-70e3-438b-bbfa-981bd3729fec · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

Improving Compositional Generation with Diffusion Models Using Lift Scores Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.637111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7536035-bcea-4510-a3bb-b1ee71c049e6 · outbound

This paper cites Section A discusses the connection between our method and Classifier-Free Guidance (CFG) (Ho & Salimans, 2022; Liu et al., 2022).

Improving Compositional Generation with Diffusion Models Using Lift Scores Section A discusses the connection between our method and Classifier-Free Guidance (CFG) (Ho & Salimans, 2022; Liu et al., 2022)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.186623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7b1fb33-74dd-4d75-9199-c17f10347ad0 · outbound

This paper cites The two formulations are equivalent in the Lagrangian sense, but CFG is not guaranteed to strictly satisfy the constraints in practice.

Improving Compositional Generation with Diffusion Models Using Lift Scores The two formulations are equivalent in the Lagrangian sense, but CFG is not guaranteed to strictly satisfy the constraints in practice

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.168104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8cf527fd-5174-4d2d-b0f4-3c43e51678f0 · outbound

This paper cites (9) In this formulation: • The first term,logp generator(x0), is our original objective.

Improving Compositional Generation with Diffusion Models Using Lift Scores (9) In this formulation: • The first term,logp generator(x0), is our original objective

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.149387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 86c264fc-2b47-47cd-9d68-ad84fdfe9244 · outbound

This paper cites The figures show the generated samples for product, mixture, and negation compositions, respectively.

Improving Compositional Generation with Diffusion Models Using Lift Scores The figures show the generated samples for product, mixture, and negation compositions, respectively

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.128711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe429c12-2162-4861-8465-89830b01208d · outbound

This paper cites Prompt to generate right images: a frog and a mouse.

Improving Compositional Generation with Diffusion Models Using Lift Scores Prompt to generate right images: a frog and a mouse

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.049191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 74e7b8e8-3e64-4ed2-b5df-60e622942a0c · outbound

This paper cites an unresolved cited work.

Improving Compositional Generation with Diffusion Models Using Lift Scores Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:17:32.084582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a4ee000-8de0-4657-933d-6232686dd886 · outbound

This paper cites an unresolved cited work.

Improving Compositional Generation with Diffusion Models Using Lift Scores Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:17:32.065844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 04a6d9d7-311c-41af-add3-575ed8039f2a · outbound

This paper cites an unresolved cited work.

Improving Compositional Generation with Diffusion Models Using Lift Scores Unresolved cited work

Reference 1000

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:17:32.103411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 13d9174e-c436-40b4-878f-5914a1ef36d2 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Improving Compositional Generation with Diffusion Models Using Lift Scores Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.643579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d5ad8b6-6d6a-4276-b504-51374d0c9403 · outbound

This paper cites If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection.

Improving Compositional Generation with Diffusion Models Using Lift Scores If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.586429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26bf1f77-fc2d-4e5e-8000-f3265ee2387b · outbound

This paper cites Diffusion Rejection Sampling.

Improving Compositional Generation with Diffusion Models Using Lift Scores Diffusion Rejection Sampling

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.610009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88352f40-6fb4-4d61-8e08-30583648d8d2 · outbound

This paper cites Interpretable Diffusion via Information Decomposition.

Improving Compositional Generation with Diffusion Models Using Lift Scores Interpretable Diffusion via Information Decomposition

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.597039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb7cb382-0009-4caa-8f82-ca7b7906e250 · outbound

This paper cites Robust Classification via a Single Diffusion Model.

Improving Compositional Generation with Diffusion Models Using Lift Scores Robust Classification via a Single Diffusion Model

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T20:17:31.569542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df17d48c-0ef0-466d-bf22-aadd956c7f6b · outbound

This paper cites D., and Tsur, S.

Improving Compositional Generation with Diffusion Models Using Lift Scores D., and Tsur, S

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:17:32.204517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 83562fa5-8bcb-4042-9937-7e92192355a3 · inbound

Catastrophic Compositional Generation: Why Vanilla Diffusion Models Fail to Extrapolate cites this paper.

Catastrophic Compositional Generation: Why Vanilla Diffusion Models Fail to Extrapolate Improving Compositional Generation with Diffusion Models Using Lift Scores

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:39:45.713217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.