Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-08T04:31:04.117380Z
Paper Citation Record · LEDGER
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation
As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.06483.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
30 of 30 outbound references displayed
- verified exact1
- verified fuzzy27
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a5105dba-fbc3-4f75-8d2c-6965d1f3b770 · outbound
This paper cites an unresolved cited work.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T04:34:31.670118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 15f07c0a-1082-435c-87ba-5b5c5d80a50e · outbound
This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-08T04:34:31.189496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cf578ae0-5b63-4779-a243-226379ebbce5 · outbound
This paper cites Polydiffuse: Polygonal shape reconstruc- tion via guided set diffusion models.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Polydiffuse: Polygonal shape reconstruc- tion via guided set diffusion models
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.636298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 91c61b83-1fe1-425a-ae5f-c8fa9b5b0353 · outbound
This paper cites ProcTHOR: Large-Scale Embodied AI Using Procedural Generation.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.589079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4aebfdf6-f2dd-40de-a00b-540537d9ca6f · outbound
This paper cites Domain-adversarial training of neural net- works.Journal of Machine Learning Research, 17(59):1–35, 2016.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Domain-adversarial training of neural net- works.Journal of Machine Learning Research, 17(59):1–35, 2016
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.598496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 434c9379-7c89-44c1-9620-5e1123daa956 · outbound
This paper cites Floor plan recon- struction from sparse views: Combining graph neural network with constrained diffusion.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Floor plan recon- struction from sparse views: Combining graph neural network with constrained diffusion
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.607937Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a809da84-bbb1-4549-9936-709accdaf621 · outbound
This paper cites Deformable polyg- onal flow matching with informed priors and hierarchical graph constraints.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Deformable polyg- onal flow matching with informed priors and hierarchical graph constraints
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.630758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation faa4b393-889e-447a-b172-5af398951d91 · outbound
This paper cites Denoising diffusion probabilistic models.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Denoising diffusion probabilistic models
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.617344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1e860676-279a-4b47-b53a-1166acaa642a · outbound
This paper cites Puzzlefusion: Unleashing the power of diffusion models for spatial puzzle solving.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Puzzlefusion: Unleashing the power of diffusion models for spatial puzzle solving
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.642095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a8f0be11-945a-4fe9-9edd-07cdae137ceb · outbound
This paper cites Graph2plan: learning floorplan generation from layout graphs.ACM Trans.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Graph2plan: learning floorplan generation from layout graphs.ACM Trans
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.621289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 08404b3b-7889-4b68-a59b-8ccd5a69b8a5 · outbound
This paper cites Cubicasa5k, March 2019.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Cubicasa5k, March 2019
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.624947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5da0f522-fe54-45f9-a4bb-d23cd455e519 · outbound
This paper cites Aria data tools.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Aria data tools
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.647080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6bf202e7-6ed3-4bbf-ba13-68a93a7c167f · outbound
This paper cites Flow matching for generative modeling.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Flow matching for generative modeling
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.640364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a1316c09-bf41-4365-9f6d-cf0aedf7a011 · outbound
This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Flow straight and fast: Learning to generate and transfer data with rectified flow
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.632466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f43af720-ef5b-4ae3-89be-aebdd7f6c9b6 · outbound
This paper cites Learning transferable features with deep adaptation networks.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Learning transferable features with deep adaptation networks
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.613093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 47e773f6-4df5-4bba-b1d4-8698910cc407 · outbound
This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.595678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 202d65e9-fab1-48ac-8c8f-3d67b59dda85 · outbound
This paper cites Scenenet rgb-d: Can 5m synthetic images beat generic imagenet pre-training on indoor segmentation? 2017.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Scenenet rgb-d: Can 5m synthetic images beat generic imagenet pre-training on indoor segmentation? 2017
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.610676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 21e6d511-1221-413c-8770-01539924e13f · outbound
This paper cites House- gan: Relational generative adversarial networks for graph-constrained house layout generation.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation House- gan: Relational generative adversarial networks for graph-constrained house layout generation
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.605186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 59e6f0f3-264e-4562-a3b0-412da4cf32da · outbound
This paper cites House-gan++: Generative adversarial layout refinement network towards intelligent computational agent for professional architects.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation House-gan++: Generative adversarial layout refinement network towards intelligent computational agent for professional architects
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.601775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 41581cb4-eb9d-4ba9-8858-235bbc16fcdb · outbound
This paper cites Learning deep object detectors from 3d models.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Learning deep object detectors from 3d models
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.627068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e9fd2718-cd2e-4d7e-8df2-8c0141bd6745 · outbound
This paper cites Housediffusion: Vector floorplan generation via a diffusion model with discrete and continuous denoising.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Housediffusion: Vector floorplan generation via a diffusion model with discrete and continuous denoising
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.619416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f4ed0873-4a60-4602-96a7-3b051a706843 · outbound
This paper cites Score-based generative modeling through stochastic differential equations.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Score-based generative modeling through stochastic differential equations
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.666314Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 29bfd3f4-79d8-47f8-9c5a-98553350eca8 · outbound
This paper cites an unresolved cited work.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T04:34:31.615176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0db03735-838a-49e4-ae2e-027b3d554281 · outbound
This paper cites Return of frustratingly easy domain adaptation.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Return of frustratingly easy domain adaptation
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.628941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4342d34e-dc5e-4fbe-9c32-bf647fda9350 · outbound
This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Domain randomization for transferring deep neural networks from simulation to the real world
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.592446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9d3e44fc-6cb1-40df-af17-474525298352 · outbound
This paper cites Training deep networks with synthetic data: Bridging the reality gap by domain randomization.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Training deep networks with synthetic data: Bridging the reality gap by domain randomization
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.623239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 20e53864-b7a3-4ba5-a3b5-89807c2607b6 · outbound
This paper cites Msd: A benchmark dataset for floor plan generation of building complexes.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Msd: A benchmark dataset for floor plan generation of building complexes
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.638172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5c6b00a1-b006-40b9-8c4f-a9b9743d7f08 · outbound
This paper cites Data-driven interior plan generation for residential buildings.ACM Transactions on Graphics (SIGGRAPH Asia), 38(6), 2019.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Data-driven interior plan generation for residential buildings.ACM Transactions on Graphics (SIGGRAPH Asia), 38(6), 2019
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.643863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ad2e0896-d883-4b20-a9a6-829786905b6c · outbound
This paper cites Structured3d: A large photo-realistic dataset for structured 3d modeling.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Structured3d: A large photo-realistic dataset for structured 3d modeling
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.673509Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1e0b6374-70bf-44e3-8b94-2f4c89d78284 · outbound
This paper cites Domain generalization: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4):4396–4415, 2023.
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation Domain generalization: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4):4396–4415, 2023
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T04:34:31.634353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.