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Paper Citation Record · LEDGER

GG-SSMs: Graph-Generating State Space Models

As of 20 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2412.12423.

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

pith.paper-citation-record.v1
2412.12423 v2

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:11:00.501033Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

68 of 68 outbound references displayed

  • verified exact0
  • verified fuzzy53
  • unresolved15
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8fdb0eb-559a-4f4c-9ea8-b9b0a37a8011 · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 1

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Source-reported events for the cited work

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Observation 2502e19f-8022-4ab4-b477-b01e7ce8d8ef · outbound

This paper cites A 2- dimensional state space layer for spatial inductive bias.

GG-SSMs: Graph-Generating State Space Models A 2- dimensional state space layer for spatial inductive bias

Reference 2

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Observation d582ac99-aeae-4c62-bf5e-76baf0c23b36 · outbound

This paper cites Retina : Low-power eye tracking with event camera and spiking hardware.

GG-SSMs: Graph-Generating State Space Models Retina : Low-power eye tracking with event camera and spiking hardware

Reference 3

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Source-reported events for the cited work

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Observation 1daa8956-fca1-4179-a977-40831533d926 · outbound

This paper cites A 240 × 180 130 db 3 µs latency global shutter spatiotemporal vision sensor.

GG-SSMs: Graph-Generating State Space Models A 240 × 180 130 db 3 µs latency global shutter spatiotemporal vision sensor

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9918315b-237e-4848-8381-b932ffde0331 · outbound

This paper cites Butler, Jonas Wulff, Garrett B.

GG-SSMs: Graph-Generating State Space Models Butler, Jonas Wulff, Garrett B

Reference 5

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Source-reported events for the cited work

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Observation 7663de30-4c28-40e6-8b71-1e71bd39942e · outbound

This paper cites A minimum spanning tree algorithm with inverse-ackermann type complexity.

GG-SSMs: Graph-Generating State Space Models A minimum spanning tree algorithm with inverse-ackermann type complexity

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 889c6443-cf76-40cd-98f0-c813f22fff82 · outbound

This paper cites 3et: Efficient event-based eye tracking using a change-based convlstm network.

GG-SSMs: Graph-Generating State Space Models 3et: Efficient event-based eye tracking using a change-based convlstm network

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c0dcbaee-7b03-4dbe-8cc5-52ed56570105 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space.

GG-SSMs: Graph-Generating State Space Models Randaugment: Practical automated data augmentation with a reduced search space

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b6712030-0108-42b1-b428-6ab57ac63181 · outbound

This paper cites Long-term Forecasting with TiDE: Time-series Dense Encoder.

GG-SSMs: Graph-Generating State Space Models Long-term Forecasting with TiDE: Time-series Dense Encoder

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a3a3c2e3-f9e6-4e76-abd4-3296822e9b27 · outbound

This paper cites Li, and Li Fei-Fei.

GG-SSMs: Graph-Generating State Space Models Li, and Li Fei-Fei

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 527f941e-259d-4ad0-9f0a-215291d83748 · outbound

This paper cites Memflow: Optical flow esti- mation and prediction with memory.

GG-SSMs: Graph-Generating State Space Models Memflow: Optical flow esti- mation and prediction with memory

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b2998587-2747-49fd-834a-8d77132df38a · outbound

This paper cites Rethinking op- tical flow from geometric matching consistent perspective.

GG-SSMs: Graph-Generating State Space Models Rethinking op- tical flow from geometric matching consistent perspective

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ee5a9f89-8f89-4c34-89cc-9ae3510eea54 · outbound

This paper cites Flownet: Learn- ing optical flow with convolutional networks.

GG-SSMs: Graph-Generating State Space Models Flownet: Learn- ing optical flow with convolutional networks

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ba0d7dcb-7412-4d6f-993e-cb22d0d32c65 · outbound

This paper cites K¨ubler, and Andrea Mazzei.

GG-SSMs: Graph-Generating State Space Models K¨ubler, and Andrea Mazzei

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 975bdb2a-34ae-4930-8072-0728231cc381 · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4874b218-baba-4443-a02e-ec8e602223fa · outbound

This paper cites Fu, Tri Dao, Khaled K.

GG-SSMs: Graph-Generating State Space Models Fu, Tri Dao, Khaled K

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7c7d09d7-33a6-4572-8dbd-e09f39ffbcc4 · outbound

This paper cites Orchard, Chiara Bar- tolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, An- drew J.

GG-SSMs: Graph-Generating State Space Models Orchard, Chiara Bar- tolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, An- drew J

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 85a8caf1-f36f-4531-b95c-0fb7d070c0a3 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

GG-SSMs: Graph-Generating State Space Models Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c55fdcab-bb57-4fc2-9471-5be11039a321 · outbound

This paper cites Mamba: Linear-time sequence mod- eling with selective state spaces.

GG-SSMs: Graph-Generating State Space Models Mamba: Linear-time sequence mod- eling with selective state spaces

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.771416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8f520e63-2ebd-44f4-9d8c-e2ebf0c38770 · outbound

This paper cites Combining recurrent, con- volutional, and continuous-time models with linear state- space layers.

GG-SSMs: Graph-Generating State Space Models Combining recurrent, con- volutional, and continuous-time models with linear state- space layers

Reference 20

Resolution
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raw_fallback, observed 2026-08-11T14:11:01.752933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1b2c0b10-9057-4e01-b328-a6cbdfaa5932 · outbound

This paper cites Efficiently mod- eling long sequences with structured state spaces.

GG-SSMs: Graph-Generating State Space Models Efficiently mod- eling long sequences with structured state spaces

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 14de0d7d-6cc3-44ab-8ee3-38b6cdee213f · outbound

This paper cites Deep residual learning for image recognition.

GG-SSMs: Graph-Generating State Space Models Deep residual learning for image recognition

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.196435Z digest=sha256:84278890b6563bfa20d4c5aa1ec050238dfd9ffc7f62df79d97ed6c63abd14fe

Observation 092531cd-4a12-4d49-b255-1a466dd182b2 · outbound

This paper cites Zigma: A dit-style zigzag mamba diffusion model.

GG-SSMs: Graph-Generating State Space Models Zigma: A dit-style zigzag mamba diffusion model

Reference 23

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raw_fallback, observed 2026-08-11T14:11:01.691962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6465e043-c21c-408f-b85b-a0845805f04a · outbound

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

GG-SSMs: Graph-Generating State Space Models LocalMamba: Visual State Space Model with Windowed Selective Scan

Reference 24

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Observation 1e1f09ac-7f1b-497e-88e2-81a4de9f599d · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 38ecc308-8719-43e0-bd71-0b7dcf60f5fe · outbound

This paper cites K ´alm´an.

GG-SSMs: Graph-Generating State Space Models K ´alm´an

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e951adef-8674-4193-9e89-3df52d733b6b · outbound

This paper cites Kipf and Max Welling.

GG-SSMs: Graph-Generating State Space Models Kipf and Max Welling

Reference 27

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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 2026-08-20T06:33:59.587034+00:00.

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Observation 2f86f256-0914-49f7-92ba-f4cc425ef75b · outbound

This paper cites Revisiting long- term time series forecasting: An investigation on linear map- ping.

GG-SSMs: Graph-Generating State Space Models Revisiting long- term time series forecasting: An investigation on linear map- ping

Reference 28

Resolution
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raw_fallback, observed 2026-08-11T14:11:01.602537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a5caccdb-498a-46ad-b374-9db073bedb3d · outbound

This paper cites itransformer: In- verted transformers are effective for time series forecasting.

GG-SSMs: Graph-Generating State Space Models itransformer: In- verted transformers are effective for time series forecasting

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.584903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c2090925-6778-40b2-9d62-7d9ba4455329 · outbound

This paper cites Vmamba: Visual state space model.

GG-SSMs: Graph-Generating State Space Models Vmamba: Visual state space model

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.557785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6463d82c-27c4-4838-86f6-70982b6e21c7 · outbound

This paper cites Swin trans- former: Hierarchical vision transformer using shifted win- dows.

GG-SSMs: Graph-Generating State Space Models Swin trans- former: Hierarchical vision transformer using shifted win- dows

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.535279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 367a300d-98f0-4733-b80b-ed2e0f2507df · outbound

This paper cites A convnet for the 2020s.

GG-SSMs: Graph-Generating State Space Models A convnet for the 2020s

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.517221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.252356Z digest=sha256:bb9fa002e43daa4d888cb09ef7507549f84adee676966cd1b36924e34eba89c0

Observation 78b0e36a-6946-4fbf-8042-afdcc9232696 · outbound

This paper cites Decoupled weight decay regularization.

GG-SSMs: Graph-Generating State Space Models Decoupled weight decay regularization

Reference 33

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unresolved
no resolver link, observed 2026-08-11T14:11:00.257856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.257856Z digest=sha256:05fe1b85d69d59df9d4c7165b0af1583b9778a204da5113b0daf124b5d5db341

Observation 7b5d4269-c61b-4bcc-af17-929e073ec00d · outbound

This paper cites Chen, Huaijin Chen, and Dongfang Liu.

GG-SSMs: Graph-Generating State Space Models Chen, Huaijin Chen, and Dongfang Liu

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.479795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 970a277e-354a-44a7-99f7-26e036bf9a1d · outbound

This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.

GG-SSMs: Graph-Generating State Space Models A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.459609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.267420Z digest=sha256:3bd9e93cf91410a72cd2aed61b9e9876e3ae82800bb4bf4cd14ba748ab972deb

Observation 20732687-f701-407f-b21c-74467f275b61 · outbound

This paper cites Downs, Preey Shah, Tri Dao, Stephen A.

GG-SSMs: Graph-Generating State Space Models Downs, Preey Shah, Tri Dao, Stephen A

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.439273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.272990Z digest=sha256:6c569a4a34cb0ff17941cd4eb8806edb818910372a8ea7ee34425b869db553f2

Observation 081749ea-23d4-46b9-8d91-d91faf0a4688 · outbound

This paper cites Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam.

GG-SSMs: Graph-Generating State Space Models Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.412513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.278689Z digest=sha256:f76ac0f7e387f3d5bb909491ff6f8b6106e769756ec56baab1e5ab31dbc82198

Observation 5b4dd3b9-308b-49a7-b628-11a8065a1ee5 · outbound

This paper cites Ssm meets video diffusion models: Efficient long-term video generation with structured state spaces,.

GG-SSMs: Graph-Generating State Space Models Ssm meets video diffusion models: Efficient long-term video generation with structured state spaces,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.393391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.283941Z digest=sha256:10d5aafabc04b651d1d4e1b77480807667567956022dc11d2e5b8854225880f7

Observation 4fed30bf-8a35-48c7-be7c-9cb94dc2dde7 · outbound

This paper cites Deep-learning-based pupil center detection and tracking technology for visible-light wearable gaze tracking devices.

GG-SSMs: Graph-Generating State Space Models Deep-learning-based pupil center detection and tracking technology for visible-light wearable gaze tracking devices

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.376533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.290564Z digest=sha256:8dd12bd9c4276ff05743f1bc5d57ffdb727a6a653f5a9f0c04e796a8de86a27f

Observation 518ded47-56e4-4f87-891a-f4914e3b7abe · outbound

This paper cites Sudderth, and Jan Kautz.

GG-SSMs: Graph-Generating State Space Models Sudderth, and Jan Kautz

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.359218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.296763Z digest=sha256:558487aa7702086b4a7db7f84bb4389d571db9e7881cf43cb9f72961e444b649

Observation bd1a2bb5-aeb8-4c51-98bb-2d9ddc897fa1 · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:11:01.339400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.301765Z digest=sha256:c8a7c6f1f3fab659f9539282b1cbddd69eeb667fe1f65efa90715db3e92e3a1a

Observation 8226d345-b88e-4bc0-b101-5a3b2b3b1ac2 · outbound

This paper cites See, Hongwei Qin, Jifeng Dai, and Hongsheng Li.

GG-SSMs: Graph-Generating State Space Models See, Hongwei Qin, Jifeng Dai, and Hongsheng Li

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.313563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.306432Z digest=sha256:50c9c42b55c103920272b8bc2dd31aed1c606302007c5638211245c23d21dfea

Observation 6e7a0c5a-d7e7-4269-9589-84c4c00804f4 · outbound

This paper cites See, Hongwei Qin, Jifeng Dai, and Hongsheng Li.

GG-SSMs: Graph-Generating State Space Models See, Hongwei Qin, Jifeng Dai, and Hongsheng Li

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.292236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.313396Z digest=sha256:e875f82f0c13415addd675142c537a87e1614554f1badc3f32e9180cc8a3a8a4

Observation 8c9a0807-e6b1-4da0-a4a7-4c6f4e22ca3b · outbound

This paper cites Smith, Andrew Warrington, and Scott Linder- man.

GG-SSMs: Graph-Generating State Space Models Smith, Andrew Warrington, and Scott Linder- man

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.268000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.318305Z digest=sha256:02e264b3bc228739f56d514f6688169c05b2737a9b2877ccfe803f8f9adcd3a0

Observation b1e195f8-8a8b-42d6-9c56-a3affe3f6c75 · outbound

This paper cites S7: Selective and simplified state space layers for sequence modeling, 2024.

GG-SSMs: Graph-Generating State Space Models S7: Selective and simplified state space layers for sequence modeling, 2024

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.248488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.324363Z digest=sha256:566b3327931e7c4d36f06307526e2ec1f974452017d21def6a3dee97cfdde5ff

Observation bb584a76-d6af-4dfd-a3d7-3f7569e8e11a · outbound

This paper cites Zhu, Guodong Guo, and Gezhong Li.

GG-SSMs: Graph-Generating State Space Models Zhu, Guodong Guo, and Gezhong Li

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.228718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.329648Z digest=sha256:9fd7fc8a89956de3b2af37739fc1951d8eec2d7eedb5d05bc8163ed5e90728a7

Observation d389e8cf-6dde-42e4-bbbd-dbd0fe6fbd44 · outbound

This paper cites Jamba-1.5: Hybrid Transformer-Mamba Models at Scale.

GG-SSMs: Graph-Generating State Space Models Jamba-1.5: Hybrid Transformer-Mamba Models at Scale

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:00.334311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.334311Z digest=sha256:579afb7b9c44b07e2a6bcdcccad506ac0044939a3a4a374bd82acd5fab452f57

Observation 4eb849e5-7519-4b88-8f4a-ab571c1d7fe4 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

GG-SSMs: Graph-Generating State Space Models Raft: Recurrent all-pairs field transforms for optical flow

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.210170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.340086Z digest=sha256:0bf3bc844ff9ed4e0f407d34d3eb00643f737df91b7d3bdf84d7a07c1d67e34a

Observation 67ed223f-9ab1-4cb3-88cf-8124f02f5224 · outbound

This paper cites Labelled pupils in the wild: a dataset for studying pupil detection in unconstrained environments.

GG-SSMs: Graph-Generating State Space Models Labelled pupils in the wild: a dataset for studying pupil detection in unconstrained environments

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.193865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.345353Z digest=sha256:19b26ca2d941107f645e359dfd596e1ef602c47a6083e58034bee30fea039f94

Observation fa9ae1b4-6628-4511-b68e-3b01ba196530 · outbound

This paper cites Train- ing data-efficient image transformers & distillation through attention.

GG-SSMs: Graph-Generating State Space Models Train- ing data-efficient image transformers & distillation through attention

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.176370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.351191Z digest=sha256:5e06e84e10a2da1854b18a0c60592cf3f815ad48612a16527aa8d32cc6b74421

Observation 849b19cf-1d6e-4c60-b956-eb8590d926d2 · outbound

This paper cites Attention is all you need.

GG-SSMs: Graph-Generating State Space Models Attention is all you need

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.156374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.358212Z digest=sha256:e1336877d0eb5bfa22c073307507ce2bb24580be4a9d2c40a3721c2cc470f936

Observation e1b4f17c-c77b-4484-a2dd-97cd14af2165 · outbound

This paper cites Is Mamba Effective for Time Series Forecasting?.

GG-SSMs: Graph-Generating State Space Models Is Mamba Effective for Time Series Forecasting?

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:00.363838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.363838Z digest=sha256:454ee15e81ffb7ba3a252455f02409ae3ebd3b5cd8b7f06c60870485df0c7ddc

Observation 1acc1c55-d050-476c-bd78-6d3dd8ad8abe · outbound

This paper cites Timesnet: Temporal 2d- variation modeling for general time series analysis.

GG-SSMs: Graph-Generating State Space Models Timesnet: Temporal 2d- variation modeling for general time series analysis

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.135535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.369799Z digest=sha256:5eeda597c3e2af9973765355c8bad2290eda9fc8a406ab3e6b198cf1da51ddfc

Observation 71b111f1-186f-4f25-971d-b6b6326d064c · outbound

This paper cites GrootVL: Tree Topology is All You Need in State Space Model.

GG-SSMs: Graph-Generating State Space Models GrootVL: Tree Topology is All You Need in State Space Model

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:00.375268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.375268Z digest=sha256:f339a9b16228b099691ad1827b4da1c42bda1504ae2889221376777e08899430

Observation 850ec9be-52d8-432a-8ce4-0abc7b3f80f3 · outbound

This paper cites Gmflow: Learning optical flow via global matching.

GG-SSMs: Graph-Generating State Space Models Gmflow: Learning optical flow via global matching

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.110739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.382689Z digest=sha256:9112935fefe1cc562d7076a42b45f25ee27a03f54527585f4bef876ce90ecbf8

Observation 2e565b43-c237-410c-b7a9-195b6e7a96f5 · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:11:01.090313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.389220Z digest=sha256:abb014bc8504bd7e371b6b98f6bcede3766cfa17f0f0620253dca9c3f71300e3

Observation 3350f5b6-d90f-481c-8ced-0e1aae02cc83 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

GG-SSMs: Graph-Generating State Space Models Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.065541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.403106Z digest=sha256:ecc5873d2750be58008d46751c6e761e2d4147b29b5a80cfec179d1fe30fb822

Observation ce657e0d-5628-460f-b576-64a1989c75b5 · outbound

This paper cites Zhang, and Qiang Xu.

GG-SSMs: Graph-Generating State Space Models Zhang, and Qiang Xu

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.041280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.423392Z digest=sha256:015ec512fa82660b0da444798ecc317e8b1b21a66df1bfb3fd902c226d5b86fd

Observation a86968ed-cb5c-4665-b7c4-920d0c475cab · outbound

This paper cites mixup: Beyond empirical risk minimization.

GG-SSMs: Graph-Generating State Space Models mixup: Beyond empirical risk minimization

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:01.018300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.431517Z digest=sha256:7c1b254fb40912d8d37f104739f09cdcf3792fbfcb6a43f784ff6555d266592e

Observation 44efd3c1-4d68-41fd-bf2e-dd1fa8531378 · outbound

This paper cites HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling.

GG-SSMs: Graph-Generating State Space Models HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:00.442638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.442638Z digest=sha256:2c357a45f1c6bd1e1f78aedc67c3425d82e72f3531494fc4cbeca8d24a5a0d6b

Observation 556e7fe9-32f5-46ff-8517-f45fda867639 · outbound

This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting.

GG-SSMs: Graph-Generating State Space Models Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.993904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.456076Z digest=sha256:8db6dd5cddc668d6b352c8b64fe163b07b55273da473d9f6c3cc4561a9837e95

Observation 0293c1c5-a8b5-4ef5-a8ee-d5855502dc05 · outbound

This paper cites Ev-eye: Rethink- ing high-frequency eye tracking through the lenses of event cameras.

GG-SSMs: Graph-Generating State Space Models Ev-eye: Rethink- ing high-frequency eye tracking through the lenses of event cameras

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.970406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.462432Z digest=sha256:f7614674d4dd93ae739f44c85c0d0948ce0af6c5626f2b6644b96f2a735e99f3

Observation 246e9cd0-e47f-499e-bd96-f18cead81966 · outbound

This paper cites an unresolved cited work.

GG-SSMs: Graph-Generating State Space Models Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:11:00.946734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.470432Z digest=sha256:0477a930e9d26d54f91f23fbaff034ca90ee06b741f30e2ce7147c7b2ca34d4b

Observation e01a7b96-74f2-4410-a59e-f7e6bda54862 · outbound

This paper cites Vision mamba: Efficient visual representation learning with bidirectional state space model.

GG-SSMs: Graph-Generating State Space Models Vision mamba: Efficient visual representation learning with bidirectional state space model

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.918076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.477143Z digest=sha256:6c21add041c80974a4e57d9f64ab9803f0293c0cdbd3ae92354099223ff95832

Observation 617bccda-2f3f-4197-ab3e-a041b7743193 · outbound

This paper cites An effective loss function for generating 3d models from single 2d image without render- ing.

GG-SSMs: Graph-Generating State Space Models An effective loss function for generating 3d models from single 2d image without render- ing

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.890105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.482339Z digest=sha256:247e0d15417d978adf359ae7ae66955d42c8a33c074ce100d4d2fe9f269a99ca

Observation 5ec50ff1-74a5-4a4a-a15b-37bb27589411 · outbound

This paper cites From chaos comes order: Ordering event rep- resentations for object recognition and detection.

GG-SSMs: Graph-Generating State Space Models From chaos comes order: Ordering event rep- resentations for object recognition and detection

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.866185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.489431Z digest=sha256:100f7e851f219fec533228d65feb7b2975020b987b95db3241fc7d683da90183

Observation ba967ad1-9c56-421a-b754-f8be74bad47a · outbound

This paper cites State space models for event cameras.

GG-SSMs: Graph-Generating State Space Models State space models for event cameras

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.833747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.494609Z digest=sha256:13375efca1842a27ae7f1b5f94c523fb87f2a177c03ff72435d64bef9d0eedcc

Observation 34baa129-8012-43e5-8218-fac9e93469fe · outbound

This paper cites Limits of deep learning: Sequence modeling through the lens of complexity theory, 2024.

GG-SSMs: Graph-Generating State Space Models Limits of deep learning: Sequence modeling through the lens of complexity theory, 2024

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:11:00.810935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T14:11:00.501033Z digest=sha256:2ae10fbcae52eefde03f869eecea1f0d604cc475b395f3b73e8c1a2856069c30

Pith citing papers

No inbound Pith citation observations are available.