Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-22T06:02:33.824296Z
Paper Citation Record · LEDGER
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders
As of 5 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2605.22777.
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 2026-08-05T06:32:48.257954+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
42 of 42 outbound references displayed
- verified exact10
- verified fuzzy31
- unresolved0
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 94745734-38a4-4a63-825a-ff93b5e4e69b · outbound
This paper cites High- resolution image synthesis with latent diffusion models.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders High- resolution image synthesis with latent diffusion models
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.408699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a63f6bad-82cb-4c87-9ab3-a0fb8197873f · outbound
This paper cites Flux.https://github.com/black-forest-labs/flux.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Flux.https://github.com/black-forest-labs/flux
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.412105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 40fc4eb8-d0cf-4bd1-a972-d6508b89a488 · outbound
This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T06:04:39.563616Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2ccd7c9c-a131-484e-86b0-a3ee0da765c8 · outbound
This paper cites Diffusion transformers with representation autoencoders.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Diffusion transformers with representation autoencoders
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.398612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ed53b390-05f9-40b0-9a69-66580d265df9 · outbound
This paper cites Dinov2: Learning robust visual features without supervision.TMLR.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Dinov2: Learning robust visual features without supervision.TMLR
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.415524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 951384ae-d9dd-423e-b9dc-9b75ab337c33 · outbound
This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T06:04:39.567961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 50da263a-1afe-4b75-8ac6-2307a3b9dcec · outbound
This paper cites Learning transferable visual models from natural language supervision.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Learning transferable visual models from natural language supervision
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.387256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 09b03789-0aef-4cb7-b089-5fbf02a71b40 · outbound
This paper cites Sigmoid loss for lan- guage image pre-training.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Sigmoid loss for lan- guage image pre-training
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.386855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 94b869df-f63b-47f0-92f2-419bf6aae860 · outbound
This paper cites DINOv3.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders DINOv3
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T06:04:39.519365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cb3cece6-2abe-4be4-a909-2d40b5103aec · outbound
This paper cites Auto-encoding variational bayes.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Auto-encoding variational bayes
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.393886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation aff78fa8-3898-4cd1-85db-0a9cb051df40 · outbound
This paper cites Neural discrete representation learning.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Neural discrete representation learning
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.418984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1dde7466-a354-4260-95ca-477befc5f549 · outbound
This paper cites Taming transformers for high-resolution image synthesis.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Taming transformers for high-resolution image synthesis
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.455003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8e78287d-ceca-4f1c-93b7-c6f317191a4f · outbound
This paper cites Unilip: Adapting clip for unified multimodal understanding, generation and editing.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Unilip: Adapting clip for unified multimodal understanding, generation and editing
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T06:04:39.553324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bafac140-6089-4381-8dfe-1c272d032eb5 · outbound
This paper cites Latent diffusion model without variational autoencoder.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Latent diffusion model without variational autoencoder
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.373234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bb97466a-d69d-427f-bc8e-d4b53c4b6818 · outbound
This paper cites Dualtoken: Towards unifying visual understanding and generation with dual visual vocabularies.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Dualtoken: Towards unifying visual understanding and generation with dual visual vocabularies
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.427140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 26c464f8-a04e-4c90-96ff-1e677a906f0d · outbound
This paper cites Aligning visual foundation encoders to tokenizers for diffusion models.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Aligning visual foundation encoders to tokenizers for diffusion models
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.422884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bbdc2c87-82f1-43ca-8f46-69c73d3bc703 · outbound
This paper cites Rpiae: A representation-pivoted autoencoder enhancing both image generation and editing.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Rpiae: A representation-pivoted autoencoder enhancing both image generation and editing
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T06:04:39.527242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7874dfd3-74aa-46cd-9edd-04a50b60a8f9 · outbound
This paper cites Improving reconstruction of representation autoencoder.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Improving reconstruction of representation autoencoder
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T06:04:39.559337Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4a1e1961-6385-4102-b525-c76c2da10b45 · outbound
This paper cites Scalable diffusion models with transformers.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Scalable diffusion models with transformers
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.383975Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5a4e9ad9-e15d-4e0a-8e10-a27a3dc87929 · outbound
This paper cites Sit: Exploring flow and diffusion-based generative models with scalable inter- polant transformers.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Sit: Exploring flow and diffusion-based generative models with scalable inter- polant transformers
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.458610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9d54a833-db76-48a0-913e-16cc69fb436f · outbound
This paper cites Representation alignment for generation: Training diffusion transformers is easier than you think.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Representation alignment for generation: Training diffusion transformers is easier than you think
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.448115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation afd1df7f-b510-408e-830c-c3b2f7b533fb · outbound
This paper cites What matters for representation alignment: Global information or spatial struc- ture? InICLR.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders What matters for representation alignment: Global information or spatial struc- ture? InICLR
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.451495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b21aa6b4-c8e5-475e-991a-5bac8933f29b · outbound
This paper cites Repa-e: Unlocking vae for end-to-end tuning with latent diffusion transformers.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Repa-e: Unlocking vae for end-to-end tuning with latent diffusion transformers
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.462046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 13e75e7f-55fb-4782-91ec-56a270fc48ff · outbound
This paper cites Representation entanglement for generation: Training diffusion transformers is much easier than you think.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Representation entanglement for generation: Training diffusion transformers is much easier than you think
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.441307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fea27401-d7ac-47bb-88ea-9d7d47a00736 · outbound
This paper cites Catok: Taming mean flows for one-dimensional causal image tokenization.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Catok: Taming mean flows for one-dimensional causal image tokenization
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.437201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ab764d0-e786-428a-a8f4-f82f6bb3e5ba · outbound
This paper cites Reconstruction vs.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Reconstruction vs
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.433851Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 02680db4-7179-4db1-8f95-61aac3c282bb · outbound
This paper cites Distribution Matching Variational AutoEncoder.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Distribution Matching Variational AutoEncoder
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T02:16:12.075701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b2bf2b4b-fb15-4ed9-aad0-1c10a50c562d · outbound
This paper cites Taming sampling perturbations with variance expansion loss for latent diffusion models.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Taming sampling perturbations with variance expansion loss for latent diffusion models
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T06:04:39.548368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cc9b2146-145a-421b-ac90-df8897645b56 · outbound
This paper cites VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T06:04:39.573208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2782fa99-0766-4ede-82ba-4f8bddf55cf1 · outbound
This paper cites Generative multimodal pretraining with discrete diffusion timestep tokens.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Generative multimodal pretraining with discrete diffusion timestep tokens
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.405469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e5d94829-5e0c-46f7-8946-26c2057f0a0d · outbound
This paper cites Scaling rectified flow trans- formers for high-resolution image synthesis.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Scaling rectified flow trans- formers for high-resolution image synthesis
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.390592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation aad30383-0db0-485d-8eaa-59e47e3355fe · outbound
This paper cites One layer is enough: Adapting pretrained visual encoders for image generation.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders One layer is enough: Adapting pretrained visual encoders for image generation
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T06:04:39.532599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8ce97d08-2c2b-4812-8640-8196ef304b70 · outbound
This paper cites Efros, Eli Shechtman, and Oliver Wang.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Efros, Eli Shechtman, and Oliver Wang
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.430575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9ae9841d-3f02-4ee1-92f7-9bb70670605e · outbound
This paper cites Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.369966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 73eeb6ce-ffcd-4250-9737-bfe7a5650ec7 · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders An image is worth 16x16 words: Transformers for image recognition at scale
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.368350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f3411643-0c13-44f2-8939-0269d476ddfb · outbound
This paper cites Imagenet: A large-scale hierarchical image database.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Imagenet: A large-scale hierarchical image database
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.364135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f5e9f9bc-45e7-4ae9-8613-a51e6cdcb2b8 · outbound
This paper cites Bovik, H.R.
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.352403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ad6aeedd-ca43-4f22-94bc-0d0f1a0f1287 · outbound
This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Gans trained by a two time-scale update rule converge to a local nash equilibrium
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.356150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1c95f0ef-f45d-4a7e-be0e-8e5e8cdf800c · outbound
This paper cites Diffusion models beat gans on image synthesis.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Diffusion models beat gans on image synthesis
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.367081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0d48e163-9b42-4b70-a1a7-af082ee73f96 · outbound
This paper cites Fast training of diffusion models with masked transformers.TMLR.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Fast training of diffusion models with masked transformers.TMLR
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.444687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3c348dc4-2d18-4628-97bb-dc200131c1d6 · outbound
This paper cites Vision transformers need registers.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Vision transformers need registers
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T06:04:40.380513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a0825f5a-32d6-425a-9fd4-7ca740552a8c · outbound
This paper cites Active Params.
DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders Active Params
Reference 42
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-22T06:04:40.402030Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
No inbound Pith citation observations are available.