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Paper Citation Record · LEDGER

Parallel Sequence Modeling via Generalized Spatial Propagation Network

As of 11 August 2026, this Paper Citation Record lists 97 of 97 outbound references and 0 inbound Pith citation observations for arXiv:2501.12381.

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

pith.paper-citation-record.v1
2501.12381 v1

Coverage vector

measured 97 of 97 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:16:43.832714Z

measured 97 of 97 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

97 of 97 outbound references displayed

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  • unresolved47
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b088bae9-501c-48de-ad41-731e975c2933 · outbound

This paper cites Xcit: Cross-covariance image transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Xcit: Cross-covariance image transformers

Reference 1

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Observation e1570967-0bba-43d0-a4c0-d86618a9f826 · outbound

This paper cites Vision-LSTM: xLSTM as Generic Vision Backbone.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Vision-LSTM: xLSTM as Generic Vision Backbone

Reference 2

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Observation 776eae95-1168-4f45-afd7-77c3422e2e57 · outbound

This paper cites Layer Normalization.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Layer Normalization

Reference 3

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Observation 003e71e0-1baf-45fc-a99a-b74b7dbbe399 · outbound

This paper cites Exploring Alternatives to Softmax Function.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Exploring Alternatives to Softmax Function

Reference 4

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Observation 408e7868-ae4f-4727-bf5c-f77e009ba776 · outbound

This paper cites All are worth words: A vit backbone for diffusion models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network All are worth words: A vit backbone for diffusion models

Reference 5

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Observation a8b3df54-5a3b-4bab-aa43-3fcfda7a1bd9 · outbound

This paper cites Multidiffusion: Fusing diffusion paths for controlled image generation.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Multidiffusion: Fusing diffusion paths for controlled image generation

Reference 6

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Observation 7447f20c-3482-4111-afa5-2274fd86a205 · outbound

This paper cites 2-D SSM: A General Spatial Layer for Visual Transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network 2-D SSM: A General Spatial Layer for Visual Transformers

Reference 7

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Observation c012fced-07fa-471a-98a4-90b841c7b220 · outbound

This paper cites Language Models are Few-Shot Learners.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Language Models are Few-Shot Learners

Reference 8

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Observation eb6d1e13-20bd-4f41-812b-24ad45aa3a74 · outbound

This paper cites Scene labeling with lstm recurrent neural net- works.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Scene labeling with lstm recurrent neural net- works

Reference 9

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Observation 00c13f63-93ad-48cc-ba8c-cd33fe934e7a · outbound

This paper cites End-to- end object detection with transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network End-to- end object detection with transformers

Reference 10

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Observation 22374cd1-60bc-41eb-956a-fb4751a3b3cd · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Emerg- ing properties in self-supervised vision transformers

Reference 11

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Observation 82a61733-453b-4ade-9fb7-5b57c9f07cc5 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

Parallel Sequence Modeling via Generalized Spatial Propagation Network PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 12

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Observation 1bbc7e8a-0bed-4768-84cc-aff03844afd6 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Generating Long Sequences with Sparse Transformers

Reference 13

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Observation adf7c6f3-bc96-4b04-99d1-b61d23a7ffe4 · outbound

This paper cites Xception: Deep learning with depthwise separable convolutions.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Xception: Deep learning with depthwise separable convolutions

Reference 14

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Observation 52c73da9-743c-4495-958e-61ed6d0d6af8 · outbound

This paper cites Rethink- ing attention with performers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Rethink- ing attention with performers

Reference 15

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Observation 09ed2203-1ad2-4df2-a4ad-64bb4e303916 · outbound

This paper cites Twins: Re- visiting the design of spatial attention in vision transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Twins: Re- visiting the design of spatial attention in vision transformers

Reference 16

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Observation c8128895-ac38-44ea-9c69-b68d82b3c7d5 · outbound

This paper cites Empirical evaluation of gated recurrent neural networks on sequence modeling.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Empirical evaluation of gated recurrent neural networks on sequence modeling

Reference 17

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Observation 9e0b21af-c068-4e7d-bc14-560e4825043c · outbound

This paper cites Coatnet: Marrying convolution and attention for all data sizes.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Coatnet: Marrying convolution and attention for all data sizes

Reference 18

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Observation eb4ef015-4b5e-49dd-afe9-4d903d838fea · outbound

This paper cites Transformers are ssms: Generalized models and efficient algorithms through structured state space duality.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Transformers are ssms: Generalized models and efficient algorithms through structured state space duality

Reference 19

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Observation e45473d1-9acd-4b8a-a207-77b80c17a11d · outbound

This paper cites Vision transformers need registers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Vision transformers need registers

Reference 20

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Observation 8e154304-9ae5-4629-9027-442f5c93740d · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Imagenet: A large-scale hierarchical image database

Reference 21

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Observation 90b6dfb7-a641-4811-b63b-6a938ce1f84d · outbound

This paper cites Diffusion models beat gans on image synthesis.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Diffusion models beat gans on image synthesis

Reference 22

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Observation 80bc5911-ed16-4db0-8262-1668ef7c77c4 · outbound

This paper cites Cswin transformer: A general vision transformer backbone with cross-shaped windows.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Cswin transformer: A general vision transformer backbone with cross-shaped windows

Reference 23

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Observation 4cd70c49-a69e-44bb-9fca-9a3969042e80 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.

Parallel Sequence Modeling via Generalized Spatial Propagation Network An image is worth 16x16 words: Trans- formers for image recognition at scale

Reference 24

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Observation 45557290-3a38-4231-a320-7890c81c7596 · outbound

This paper cites Demofusion: Democratising high- resolution image generation with no $$$.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Demofusion: Democratising high- resolution image generation with no $$$

Reference 25

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Observation 6b21cd99-d6c2-4932-8126-7e606c217929 · outbound

This paper cites Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures

Reference 26

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Observation cf8f735f-8c61-490a-8a96-abc4a2b9f67d · outbound

This paper cites Sigmoid- weighted linear units for neural network function approxi- mation in reinforcement learning.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Sigmoid- weighted linear units for neural network function approxi- mation in reinforcement learning

Reference 27

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Observation ce65f3c7-211a-4d8b-871e-c168f3cd0389 · outbound

This paper cites Hungry hungry hippos: Towards language modeling with state space models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Hungry hungry hippos: Towards language modeling with state space models

Reference 28

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Observation a5745010-9f0a-45c8-a38d-7dfdbd6cecb6 · outbound

This paper cites Levit: a vision transformer in convnet’s clothing for faster inference.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Levit: a vision transformer in convnet’s clothing for faster inference

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 13c7257c-0f23-4cf1-b3db-b21d5fe2de72 · outbound

This paper cites Multi-dimensional recurrent neural networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Multi-dimensional recurrent neural networks

Reference 30

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e06d9a61-92eb-4acd-a2bf-a428cf0a8449 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 31

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Observation 77c37199-f950-4322-8a63-63f30cec4221 · outbound

This paper cites Elasticdiffusion: Training-free arbitrary size image generation through global-local content separation.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Elasticdiffusion: Training-free arbitrary size image generation through global-local content separation

Reference 32

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raw_fallback, observed 2026-08-10T17:16:45.001859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 5a13a5c6-a7d9-4146-a3b0-259be74ab62c · outbound

This paper cites Flatten transformer: Vision transformer using focused linear attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Flatten transformer: Vision transformer using focused linear attention

Reference 33

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raw_fallback, observed 2026-08-10T17:16:44.988311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 87326f92-72b2-4b8f-98f2-1c92fae584fb · outbound

This paper cites MambaVision: A Hybrid Mamba-Transformer Vision Backbone.

Parallel Sequence Modeling via Generalized Spatial Propagation Network MambaVision: A Hybrid Mamba-Transformer Vision Backbone

Reference 34

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Observation 7a08da87-4605-4f38-9290-ab41cb5ee82d · outbound

This paper cites Zhang, Shaoqing Ren, and Jian Sun.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Zhang, Shaoqing Ren, and Jian Sun

Reference 35

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raw_fallback, observed 2026-08-10T17:16:44.974962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6b8af26e-922c-448c-ac67-f5886ebfe364 · outbound

This paper cites Scalecrafter: Tuning-free higher- resolution visual generation with diffusion models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Scalecrafter: Tuning-free higher- resolution visual generation with diffusion models

Reference 36

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raw_fallback, observed 2026-08-10T17:16:44.963198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 79777a7c-1fdc-4dab-91c8-aa9f078f638b · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Parallel Sequence Modeling via Generalized Spatial Propagation Network Gaussian Error Linear Units (GELUs)

Reference 37

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Observation 897ef724-3483-4322-89cf-255dcad4be4a · outbound

This paper cites Tenenbaum, Kfir Aberman, Y.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Tenenbaum, Kfir Aberman, Y

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.951301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.565041Z digest=sha256:66b409ebbbf5631ed0627965b5739576a4c03da375b000ec016b9d339344fb72

Observation 0974efd4-ca55-4341-b997-8ade7ab0012f · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.939851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.569850Z digest=sha256:46f6e9e6ccd5a281c54b061106fd524a58c8d34e2ce19b019113e8d7966baa94

Observation 09ed3a0e-126a-427a-bbad-e79c63106236 · outbound

This paper cites Classifier-free diffusion guidance.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Classifier-free diffusion guidance

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.927898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.573893Z digest=sha256:7dea94a3865a76f10d43328ae946c367bbaaac545c1d9a567a598c8fc2a28809

Observation d6284e6d-6289-4c6d-ae0f-568c9c9b5079 · outbound

This paper cites Axial Attention in Multidimensional Transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Axial Attention in Multidimensional Transformers

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.577661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.577661Z digest=sha256:63cb806f2cf2556ed5783443fcd30635fc4861da9f681f746034ebbe85502101

Observation c20fd6d6-d65c-413b-a793-1216c3018a81 · outbound

This paper cites Untersuchungen zu dynamischen neu- ronalen netzen.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Untersuchungen zu dynamischen neu- ronalen netzen

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.916234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.582822Z digest=sha256:e88a1ac61e03026af79c5fe55af8bd14b4aab37cc30ab714a0b3fc562d90d1bf

Observation 6ad41833-80aa-45cd-95f9-35490315aeb8 · outbound

This paper cites Long short-term memory.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Long short-term memory

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.903300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.587750Z digest=sha256:5a0f4a7de57269c781e13bd5c935bb974c9c6e326bd066a891d7ced2ee44e8b7

Observation 5663af35-946c-4388-a3fa-2fc268e713c6 · outbound

This paper cites Trans- former quality in linear time.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Trans- former quality in linear time

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.891409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.591897Z digest=sha256:79c62c23562c9b70df18c3504c71e49b537c2de25f574c264068cbf8caa4c961

Observation 89c5aa19-5d14-4021-acb8-34845ecc3c87 · outbound

This paper cites FouriScale: A Frequency Perspective on Training-Free High-Resolution Image Synthesis.

Parallel Sequence Modeling via Generalized Spatial Propagation Network FouriScale: A Frequency Perspective on Training-Free High-Resolution Image Synthesis

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.596261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.596261Z digest=sha256:825094f98e64a48cc027debcee7c3fb36782988a72a1f714fcf273984b987fa5

Observation 0a42e1ef-56d5-4882-aae1-b4420737a82e · outbound

This paper cites LocalMamba: Visual State Space Model with Windowed Selective Scan.

Parallel Sequence Modeling via Generalized Spatial Propagation Network LocalMamba: Visual State Space Model with Windowed Selective Scan

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.600372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.600372Z digest=sha256:7e71fcfdf53181fb1177ac6ef224ade55d3febe8212ec0043ccdf1d422a859ce

Observation 0a3d13ef-5fb0-4b85-aa15-1a04462be04a · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.879048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.604545Z digest=sha256:abe0f7dff58eb331271c8bc9ee205f6e06b12eebce06abdab22d7b56c8011ab4

Observation fae2b8a8-d803-460e-8f62-c8d44c0d5568 · outbound

This paper cites Bk-sdm: Architecturally compressed stable diffusion for efficient text-to-image generation.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Bk-sdm: Architecturally compressed stable diffusion for efficient text-to-image generation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.867508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.608348Z digest=sha256:e750827cb13a7dc63d15bcd54d4eb28c127437ec168c3a33abe24e20c2999505

Observation c54178ff-869d-49e5-9c9e-8d7c76f02769 · outbound

This paper cites Re- former: The efficient transformer.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Re- former: The efficient transformer

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.855137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.612373Z digest=sha256:74600bed919ca33e7cad798b295f4234f76248612991646012484fdbd939b432

Observation ae3bc44d-e900-43a9-8af3-030010ad23cf · outbound

This paper cites Chatgpt: Jack of all trades, master of none.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Chatgpt: Jack of all trades, master of none

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.843098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.616552Z digest=sha256:09c1c2c9fcd6a0ab868da865840f0496a920365ae89eab793bbf1a4b75f43c0f

Observation b6dfa10c-7908-4266-b442-5959c0d7f9a7 · outbound

This paper cites Im- agenet classification with deep convolutional neural networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Im- agenet classification with deep convolutional neural networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.830813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.620343Z digest=sha256:d781ef54e6a5f1ef64d71b05a765f0a1e3d5fcb0320d04f66fcc1ecb8f721cd7

Observation 2a4671a3-4514-4685-84db-4cc7867829ed · outbound

This paper cites Improved precision and recall metric for assessing generative models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Improved precision and recall metric for assessing generative models

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.816107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.625432Z digest=sha256:1b2c2e7ba5a00e1dc3c073716e0ba8e4d6473eb52d83688a9112721848abea11

Observation 5fdaa095-ca5e-4259-a662-9a9aba734c93 · outbound

This paper cites Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.629784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.629784Z digest=sha256:69edacb133da6adc7ab3cadb6848651a352ccf1452e49b571ee95c1ce37c5ffe

Observation 79ec935c-8623-4ff4-b340-00ad69bfc36a · outbound

This paper cites Savarese, and Steven C.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Savarese, and Steven C

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.800516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.633867Z digest=sha256:5a46419ef31518bd7f7f75d7857157e215e9eba6b3c2e3247ad2e0e88aa8b022

Observation b88dec22-7342-4054-9d75-43651ae2beb1 · outbound

This paper cites Uniformer: Unified transformer for efficient spatiotemporal representation learning.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Uniformer: Unified transformer for efficient spatiotemporal representation learning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.787677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.637888Z digest=sha256:bcbe7a7e8c6e84010eef0fd1c4f9509aa0268f01c835e4fc023a4bf720df8b80

Observation 79b0a1f3-c0fc-44b1-bc50-95e7f8598699 · outbound

This paper cites Distrifusion: Distributed parallel inference for high-resolution diffusion models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Distrifusion: Distributed parallel inference for high-resolution diffusion models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.775288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.641588Z digest=sha256:8178cbbe36a924571c156d2276f7aaa50c85be118195ca6d4ff269ad3c6a9233

Observation c1729834-8a03-4407-aed4-4c02cec13f16 · outbound

This paper cites Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.645614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.645614Z digest=sha256:f24265dd6f3254652c506a41ebc6aa2ee79ac7cf63cd686822976efece96e030

Observation ac6bb3e4-c90e-4bdc-945a-5fcdaeb5e227 · outbound

This paper cites CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation Method.

Parallel Sequence Modeling via Generalized Spatial Propagation Network CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation Method

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.650370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.650370Z digest=sha256:cb140c5af624e38f75391daf95ba8d702c875042d0e0167ac7f95cc5016f2366

Observation 508598c8-baa1-4db2-be63-2ae47580764c · outbound

This paper cites Microsoft coco: Common objects in context.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Microsoft coco: Common objects in context

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.761573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.654524Z digest=sha256:063514e60446964d4645dcf7e52e6d2ce784b6f0966e2b0c302bcdeea60f4159

Observation 180fabdb-f7ce-4ab5-9a53-085ad9e4fcaf · outbound

This paper cites AccDiffusion: An Accurate Method for Higher-Resolution Image Generation.

Parallel Sequence Modeling via Generalized Spatial Propagation Network AccDiffusion: An Accurate Method for Higher-Resolution Image Generation

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.658432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.658432Z digest=sha256:f99289ec77370f7372fb491aa7ea3c5a622f8d07c6968d0ac58eafe84c880e4a

Observation e90126f3-2f0f-44e5-91c4-bbf363bf01e1 · outbound

This paper cites Transformer-vq: Linear-time transformers via vector quantization.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Transformer-vq: Linear-time transformers via vector quantization

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.747037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.662949Z digest=sha256:3d86cd6c1fe422b3be31a23e1ac61db1632ce449d792c1b1659060a49d54db43

Observation fc16ac80-879f-47f1-baa3-18e63a3d816c · outbound

This paper cites Learning affinity via spatial propagation networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Learning affinity via spatial propagation networks

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.730049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.667894Z digest=sha256:e0e7320b98dcec9210a565ddbf54150435d2b0c718f7218c7834d070fbcad42f

Observation fa2c8bcd-df98-43d8-a1c8-066f1b21ff69 · outbound

This paper cites LinFusion: 1 GPU, 1 Minute, 16K Image.

Parallel Sequence Modeling via Generalized Spatial Propagation Network LinFusion: 1 GPU, 1 Minute, 16K Image

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.672571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.672571Z digest=sha256:46c98e9e2fac6c2148950a19f1eaedb6d0bcca2340aa4b7dd16209609d933f4a

Observation 2703d1fd-5d76-42b0-b006-5fc40c2c5991 · outbound

This paper cites VMamba: Visual State Space Model.

Parallel Sequence Modeling via Generalized Spatial Propagation Network VMamba: Visual State Space Model

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.677642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.677642Z digest=sha256:c263d62d5fdad42db5572e5244c45f997010f5b7b1ecf8027566abccd885e574

Observation 79aeff2d-a600-48eb-891a-b6fadfa10e32 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Swin transformer: Hierarchical vision transformer using shifted windows

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.713443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.683211Z digest=sha256:2e73a79fc42c616fe5c4e9a31af64f980a2db0f9133cf4ecbb485693d0ce3d4b

Observation bddf03a3-44a2-4428-a8d4-e58399270c23 · outbound

This paper cites A convnet for the 2020s.

Parallel Sequence Modeling via Generalized Spatial Propagation Network A convnet for the 2020s

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.699452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.688473Z digest=sha256:0f148b5f62f7241360ad09a0c617019f8fc7fd41ef906456bcef3438195cf8fd

Observation 7d959d22-f33f-41c5-a84f-36f027d02069 · outbound

This paper cites Soft: Softmax-free transformer with linear complexity.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Soft: Softmax-free transformer with linear complexity

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.684210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.693002Z digest=sha256:b95d831964d3012a2fc64390acfe4cf018f7948fd4c31071a28da4f773311653

Observation df0b005d-5a93-4e7b-9c63-cc66a683b850 · outbound

This paper cites Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.668329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.697981Z digest=sha256:ae1577934a483ae95ccc736ba1d3c7935e6ab98f6ee7f4b2a6c4ceba41b6ca4a

Observation 7522fff4-531d-4f65-9623-b11658fd6bbf · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Parallel Sequence Modeling via Generalized Spatial Propagation Network SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.701779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.701779Z digest=sha256:a6595c071fad0c15639871c95502702fdfa40e9758d9acad498e8bc298540b64

Observation 736f728d-acef-4d38-b110-d6fd854235a1 · outbound

This paper cites Generating Images with Sparse Representations.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Generating Images with Sparse Representations

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.706301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.706301Z digest=sha256:5249e42773625a14b68f72a675688e2d7372361474e0a7edbc0d77a08c53eab2

Observation 67e87668-5f5c-4127-97af-51fd0b90ecf2 · outbound

This paper cites S4nd: Modeling images and videos as multidimensional signals with state spaces.

Parallel Sequence Modeling via Generalized Spatial Propagation Network S4nd: Modeling images and videos as multidimensional signals with state spaces

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.656079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.710550Z digest=sha256:23e0d163d9875d9d4b83a33aada19f52ca9a3d3504b7ef590b0b690d322c6b5d

Observation 3f8bfb4e-0524-4973-8aef-38d520591d3b · outbound

This paper cites On aliased resizing and surprising subtleties in gan evaluation.

Parallel Sequence Modeling via Generalized Spatial Propagation Network On aliased resizing and surprising subtleties in gan evaluation

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.714866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.714866Z digest=sha256:9b000339bbe3ddc0ecb545fdc9a84226fcfd616c93cf1f1e5147dd892f7caa51

Observation 87a91003-5e8c-4af0-b616-e09cd4f9342c · outbound

This paper cites On the difficulty of training recurrent neural networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network On the difficulty of training recurrent neural networks

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.634362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.719148Z digest=sha256:2fa519b8404ae540e57e204b89cff153ad7108f8b10f5b9285200a5d6c78c452

Observation 25ac1bce-a612-46a3-9b80-23019bf1fa42 · outbound

This paper cites Scalable diffusion models with transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Scalable diffusion models with transformers

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.614810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.724278Z digest=sha256:f4f0eb00ab31a264090ff038c86691045357ca7468115134fa75110bec39c292

Observation 717539f0-589f-4ea6-98f4-2dd066956698 · outbound

This paper cites Random Feature Attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Random Feature Attention

Reference 75

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no resolver link, observed 2026-08-10T17:16:43.729920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 79186a72-a78c-49b8-8cae-430b299ca895 · outbound

This paper cites Self-attention Does Not Need $O(n^2)$ Memory.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Self-attention Does Not Need $O(n^2)$ Memory

Reference 76

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no resolver link, observed 2026-08-10T17:16:43.734351Z

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Unavailable: canonical work link unavailable.

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Observation dc98df41-7156-4be2-9cda-b1aab9544504 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network High-resolution image synthesis with latent diffusion models

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.595712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e7a9828d-51fd-477d-b476-eab62c7c5272 · outbound

This paper cites Improved techniques for training gans.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Improved techniques for training gans

Reference 78

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.582278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 29170875-8ba1-4fff-b880-8cd5e2541d07 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next gener- ation image-text models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Laion-5b: An open large-scale dataset for training next gener- ation image-text models

Reference 79

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 300eca2b-2a13-45bd-8fb1-2eadea8ec433 · outbound

This paper cites Efficient attention: Attention with linear complexities.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Efficient attention: Attention with linear complexities

Reference 80

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e2a58164-275a-4b7c-b06e-7c5957ba5c27 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Roformer: Enhanced transformer with rotary position embedding

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.543409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4b4d91ec-b6f1-4fad-827a-da43fb5dcaec · outbound

This paper cites Training data-efficient image transformers & distillation through atten- tion.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Training data-efficient image transformers & distillation through atten- tion

Reference 82

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.529674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.763799Z digest=sha256:bef4cea35c14499fcebf18d3c6dd88946530943eb95be0cca66cafe83b4a2439

Observation a5e75e7b-9ba4-4165-9333-aff4e8dfc56e · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Parallel Sequence Modeling via Generalized Spatial Propagation Network LLaMA: Open and Efficient Foundation Language Models

Reference 83

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unresolved
no resolver link, observed 2026-08-10T17:16:43.769076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.769076Z digest=sha256:4003b56833391da6882f26b9518763196b737f95e3591fe0e37c1299e98a79a0

Observation 8dd0284e-9487-4e62-9890-65ee891a69f4 · outbound

This paper cites Pixel recurrent neural networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Pixel recurrent neural networks

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.516291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.773444Z digest=sha256:252e6dd250ede88e554696cfae3a6df3d240a9b86fd7d1b141bbe42c2dbce7ad

Observation 6d5f372e-046c-4613-8814-80bd5892cf74 · outbound

This paper cites Attention is all you need.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Attention is all you need

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.503039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.777447Z digest=sha256:649fdffe14b81095626b4b6ca1ec9f223ca6f6a7ae7be28b34d8c4267c4dac54

Observation 14fdecaa-5232-4ae4-ab59-f7908e4383a4 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Linformer: Self-Attention with Linear Complexity

Reference 86

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unresolved
no resolver link, observed 2026-08-10T17:16:43.783072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.783072Z digest=sha256:d8ac6c8eefaff66d2e312cf513f51bc643ff7c0c8683759a08735071976589a9

Observation 8fce0389-79bc-4820-89ce-364a01f335d0 · outbound

This paper cites Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.487466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.788498Z digest=sha256:e00f9336068df06043a3d33a6f13d1d21f0a2f04f75db7af881b57621fbb7601

Observation fc5ce58e-9ef8-44ef-8d40-67612d96781b · outbound

This paper cites Con- vnext v2: Co-designing and scaling convnets with masked autoencoders.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Con- vnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.473738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.792615Z digest=sha256:2cfc51b2bcfb8389b7d9e4dfaf521a32ba65ae82f9610ace92453c986799fab8

Observation 38dedc91-c6a1-429c-95b4-89e2d1d24ab7 · outbound

This paper cites Cvt: Introducing convolutions to vision transformers.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Cvt: Introducing convolutions to vision transformers

Reference 89

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verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.455870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.796760Z digest=sha256:7932306b76b006bf337e52368c3ab7bdec5a6a88df80fca0f6d9da45dec84240

Observation 34bbded4-682f-49a3-bc23-7602f0512c47 · outbound

This paper cites Lite transformer with long-short range attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Lite transformer with long-short range attention

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.438584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.801245Z digest=sha256:727c9cfc72bcbfe8e2eace59dccd24554767b716b2e2e22a7ca77ff3f80c6be9

Observation f7faab3f-9db5-467f-90af-bc976ffecf6d · outbound

This paper cites Nystr¨omformer: A nystr ¨om-based algorithm for approximat- ing self-attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Nystr¨omformer: A nystr ¨om-based algorithm for approximat- ing self-attention

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.423792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.805026Z digest=sha256:7cc8c1844fe0e8625a7917c9b67c82333df69db2dc6b05352ba26277b78be52f

Observation cf17c6d4-76b9-4ccd-bb92-a2f270e9ec41 · outbound

This paper cites Focal modulation networks.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Focal modulation networks

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.406754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.809198Z digest=sha256:d548481b19f33a8b82e0137c5f8e18058b77ee3e0ec6d7ff53080a342fb7790c

Observation b4099f2e-ff85-4067-b79a-386526391afd · outbound

This paper cites EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision.

Parallel Sequence Modeling via Generalized Spatial Propagation Network EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

Reference 93

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no resolver link, observed 2026-08-10T17:16:43.813426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.813426Z digest=sha256:ec88caf5d878df4abb1b3936afc90a7f35104a1a432eab7f47036002e6cb12c2

Observation d8f900cf-bd27-4e95-a328-be46ced3f060 · outbound

This paper cites MambaOut: Do We Really Need Mamba for Vision?.

Parallel Sequence Modeling via Generalized Spatial Propagation Network MambaOut: Do We Really Need Mamba for Vision?

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:43.818342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.818342Z digest=sha256:3c55039aaf9d479a32a35f6d3f1eed8724168d71f359a003fade859a6dd94989

Observation a3f51b9f-4ffb-4740-89df-ca1e35e5007f · outbound

This paper cites Tay, Jiashi Feng, and Shuicheng Yan.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Tay, Jiashi Feng, and Shuicheng Yan

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.391213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.822682Z digest=sha256:c55f0812909e6b5412bec2281259760974bcf37627b322557baff5fffc75e408

Observation 2ec2ae04-0149-4365-8595-26e247db2c20 · outbound

This paper cites Biformer: Vision transformer with bi-level routing attention.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Biformer: Vision transformer with bi-level routing attention

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:16:44.376567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T17:16:43.826992Z digest=sha256:6d9915067d03ce0cb53928de68c97bb50e281084e0e47dc4fe5601f3a1990f32

Observation 3338b945-a4f9-4a25-9223-85f82432f7fa · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 97

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unresolved
no resolver link, observed 2026-08-10T17:16:43.832714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.832714Z digest=sha256:57c898151d86ad86d2ede3dbb0c8d3dba0da247fdd1b11ec3d71de8a3e6a66ad

Pith citing papers

No inbound Pith citation observations are available.