SchoenbAt: Rethinking Attention with Polynomial basis | Paper Citation Record

Observation a451df90-379b-4319-a91d-32e8abd6cb23 · outbound

This paper cites Neural machine translation by jointly learning to align and translate.

SchoenbAt: Rethinking Attention with Polynomial basis Neural machine translation by jointly learning to align and translate

Reference 1

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Observation 891b3d9e-0022-4faa-a32d-1a4b0a4ae00a · outbound

This paper cites Cross-lingual language model pretraining.

SchoenbAt: Rethinking Attention with Polynomial basis Cross-lingual language model pretraining

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.182626Z

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Observation 44195066-9c01-4f58-9f60-6870488e188c · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022.

SchoenbAt: Rethinking Attention with Polynomial basis Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:58.955393Z

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Observation 3f448061-c72f-4d95-8a5b-badc5a5e1fcd · outbound

This paper cites Training language models to follow instructions with human feedback.

SchoenbAt: Rethinking Attention with Polynomial basis Training language models to follow instructions with human feedback

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.129651Z

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Observation 299efb8a-f81c-40d7-b5d6-e9aedae152a1 · outbound

This paper cites Dynamic perceiver for efficient visual recognition.

SchoenbAt: Rethinking Attention with Polynomial basis Dynamic perceiver for efficient visual recognition

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.106164Z

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Observation 2271a6c9-8802-4483-91db-87bec503908e · outbound

This paper cites Learning to weight samples for dynamic early-exiting networks.

SchoenbAt: Rethinking Attention with Polynomial basis Learning to weight samples for dynamic early-exiting networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.078662Z

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Observation 18ab731a-7b7b-44e7-a53c-7394a5896d9b · outbound

This paper cites Contrastive language-image pre- training with knowledge graphs.NeurIPS 35, 2022.

SchoenbAt: Rethinking Attention with Polynomial basis Contrastive language-image pre- training with knowledge graphs.NeurIPS 35, 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.056653Z

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Observation fe67d51f-4385-442c-bb7c-46af1b92f2f5 · outbound

This paper cites Gsva: Generalized segmentation via multimodal large language models.

SchoenbAt: Rethinking Attention with Polynomial basis Gsva: Generalized segmentation via multimodal large language models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:58.988651Z

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Observation b2585b4d-29d4-4c72-94aa-f0195c09c194 · outbound

This paper cites ResaPred: A deep residual network with self-attention to predict protein flexibility.

SchoenbAt: Rethinking Attention with Polynomial basis ResaPred: A deep residual network with self-attention to predict protein flexibility

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:01.012571Z

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Observation df4ab51d-ec31-4989-8ac6-950879d72e44 · outbound

This paper cites MCHAN: Prediction of human microbe- drug associations based on multiview contrastive hypergraph attention network.Current Bioinformatics, 20(1):70–86, 2025.

SchoenbAt: Rethinking Attention with Polynomial basis MCHAN: Prediction of human microbe- drug associations based on multiview contrastive hypergraph attention network.Current Bioinformatics, 20(1):70–86, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.991503Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89709b69-2686-4ccc-866e-15d40614e883 · outbound

This paper cites Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL.Briefings in Bioinformatics, 26(1):bbae703, 2025.

SchoenbAt: Rethinking Attention with Polynomial basis Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL.Briefings in Bioinformatics, 26(1):bbae703, 2025

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.953910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 002d93e5-b2ea-4427-b4b7-cfe5bb86b173 · outbound

This paper cites Attention is all you need.

SchoenbAt: Rethinking Attention with Polynomial basis Attention is all you need

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.927253Z

Source-reported events for the cited work

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Observation 93ddd025-9fa0-4ae3-b232-dcc1a245de55 · outbound

This paper cites A brief overview of ChatGPT: The history, status quo and potential future development.IEEE/CAA Journal of Automatica Sinica, 10(5):1122–1136, 2023.

SchoenbAt: Rethinking Attention with Polynomial basis A brief overview of ChatGPT: The history, status quo and potential future development.IEEE/CAA Journal of Automatica Sinica, 10(5):1122–1136, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.907798Z

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Observation e312b790-5829-496f-8de5-2179a4e4ee42 · outbound

This paper cites DeepSeek-V3 Technical Report.

SchoenbAt: Rethinking Attention with Polynomial basis DeepSeek-V3 Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.052473Z

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Observation 2e92d150-9f6c-4b6a-a096-c1ff539dbd7e · outbound

This paper cites Qwen2.5 Technical Report.

SchoenbAt: Rethinking Attention with Polynomial basis Qwen2.5 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.062051Z

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Observation c43513b6-50a4-4749-b8b4-1b929fdab06a · outbound

This paper cites Transformers are Rnns: fast autoregressive transformers with linear attention.

SchoenbAt: Rethinking Attention with Polynomial basis Transformers are Rnns: fast autoregressive transformers with linear attention

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.888367Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d69ef8cf-5b1f-41e9-9e1f-c93bf171836c · outbound

This paper cites Transformer dissection: An unified understanding for transformer‘s attention via the lens of kernel.

SchoenbAt: Rethinking Attention with Polynomial basis Transformer dissection: An unified understanding for transformer‘s attention via the lens of kernel

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.866802Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ef8172c6-c765-497f-9fa1-1113e83ccd33 · outbound

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

SchoenbAt: Rethinking Attention with Polynomial basis Linformer: Self-Attention with Linear Complexity

Reference 19

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Observation 90db95bd-b5f3-48d7-b604-ae0c7cc31070 · outbound

This paper cites Nyströmformer: A nyström-based algorithm for approximating self-attention.

SchoenbAt: Rethinking Attention with Polynomial basis Nyströmformer: A nyström-based algorithm for approximating self-attention

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.092688Z

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Observation 1870d000-f2f5-4833-890c-6619f4cad313 · outbound

This paper cites Skyformer: Remodel self-attention with gaussian kernel and Nyström method.

SchoenbAt: Rethinking Attention with Polynomial basis Skyformer: Remodel self-attention with gaussian kernel and Nyström method

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.824103Z

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Observation cb6de7a4-008e-4389-ab87-f23ffabeefa9 · outbound

This paper cites Primal-attention: Self-attention through asymmetric kernel svd in primal representation.

SchoenbAt: Rethinking Attention with Polynomial basis Primal-attention: Self-attention through asymmetric kernel svd in primal representation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.793031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4cfe2420-d57d-4fc8-8e09-60e89b7cac37 · outbound

This paper cites Large-kernel attention for 3D medical image segmentation.Cognitive Computation, 16(4):2063–2077, 2024.

SchoenbAt: Rethinking Attention with Polynomial basis Large-kernel attention for 3D medical image segmentation.Cognitive Computation, 16(4):2063–2077, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.767028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2e872adf-9a76-4a0e-bc03-9935a64690da · outbound

This paper cites Large kernel spectral and spatial attention networks for hyperspectral image classification.IEEE Transactions on Geoscience and Remote Sensing, 61:1–15, 2023.

SchoenbAt: Rethinking Attention with Polynomial basis Large kernel spectral and spatial attention networks for hyperspectral image classification.IEEE Transactions on Geoscience and Remote Sensing, 61:1–15, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.740310Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation beb22dca-f76a-4dc4-b524-2ab03cfe66c5 · outbound

This paper cites Interscience Publishers, 1962.

SchoenbAt: Rethinking Attention with Polynomial basis Interscience Publishers, 1962

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.718683Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6d99fe29-fed0-402b-9c92-bfa3cfaa2ee9 · outbound

This paper cites Random features for large-scale kernel machines.NeurIPS 20, 2007.

SchoenbAt: Rethinking Attention with Polynomial basis Random features for large-scale kernel machines.NeurIPS 20, 2007

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.674121Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7874cc0c-906e-4af3-8c3a-a76e189c87f3 · outbound

This paper cites Learning with SGD and random features.

SchoenbAt: Rethinking Attention with Polynomial basis Learning with SGD and random features

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.648462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9b75e08d-67ff-4d87-b5bc-9870c02d6948 · outbound

This paper cites Local random feature approximations of the Gaussian kernel.

SchoenbAt: Rethinking Attention with Polynomial basis Local random feature approximations of the Gaussian kernel

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.616340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 80c5a9fa-79c1-4099-9ed4-0f0652479112 · outbound

This paper cites New random projections for isotropic kernels using stable spectral distributions.arXiv:2411.02770, 2024.

SchoenbAt: Rethinking Attention with Polynomial basis New random projections for isotropic kernels using stable spectral distributions.arXiv:2411.02770, 2024

Reference 29

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Observation fe861e8f-cc83-4d3e-a9ba-2fd9c4e57fb2 · outbound

This paper cites Random feature maps for the itemset kernel.

SchoenbAt: Rethinking Attention with Polynomial basis Random feature maps for the itemset kernel

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.592464Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 261c71d1-4af2-4a53-9486-c65f3af1b9e3 · outbound

This paper cites Explicit Approximations of the Gaussian Kernel.

SchoenbAt: Rethinking Attention with Polynomial basis Explicit Approximations of the Gaussian Kernel

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.181953Z

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Observation 779411db-657f-4e46-92e1-8f93d2c633b6 · outbound

This paper cites Random feature attention.

SchoenbAt: Rethinking Attention with Polynomial basis Random feature attention

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.565170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a8d8c44f-d005-42d0-970e-e812faf042fd · outbound

This paper cites Rethinking attention with performers.

SchoenbAt: Rethinking Attention with Polynomial basis Rethinking attention with performers

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.204180Z

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Observation b8cf9eaf-4b57-4f89-b454-4814bee2237c · outbound

This paper cites Learning Expressive Random Feature Models via Parametrized Activations.

SchoenbAt: Rethinking Attention with Polynomial basis Learning Expressive Random Feature Models via Parametrized Activations

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:41:59.655815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 20281c9b-6603-4017-81ab-1c5a2c03e1b3 · outbound

This paper cites Random maclaurin feature-based fuzzy clustering.

SchoenbAt: Rethinking Attention with Polynomial basis Random maclaurin feature-based fuzzy clustering

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.523945Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 088ead41-4f30-485a-8b29-cb46d1c111ec · outbound

This paper cites Learning dot-product polynomials for multiclass problems.

SchoenbAt: Rethinking Attention with Polynomial basis Learning dot-product polynomials for multiclass problems

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.497380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a757518-a59e-4a21-9d3b-e07ad3d24e6e · outbound

This paper cites an unresolved cited work.

SchoenbAt: Rethinking Attention with Polynomial basis Unresolved cited work

Reference 37

Resolution: verified exact; raw_fallback, observed 2026-08-15T20:41:59.607146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 92a90440-c814-4977-ae61-b025a30f6b37 · outbound

This paper cites Positive definite functions on spheres.Duke Mathematical Journal, 9(1):96–108, 1942.

SchoenbAt: Rethinking Attention with Polynomial basis Positive definite functions on spheres.Duke Mathematical Journal, 9(1):96–108, 1942

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.472794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89aed372-8bef-484b-b417-922bca5b7c73 · outbound

This paper cites Functions of positive and negative type, and their connection with the theory of integral equations.Philosophical Transactions of the Royal Society A, 209:415–446, 1909.

SchoenbAt: Rethinking Attention with Polynomial basis Functions of positive and negative type, and their connection with the theory of integral equations.Philosophical Transactions of the Royal Society A, 209:415–446, 1909

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.447516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 55ffde62-d332-4be7-a505-249115280987 · outbound

This paper cites Random feature maps for dot product kernels.

SchoenbAt: Rethinking Attention with Polynomial basis Random feature maps for dot product kernels

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.424531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3103237-51ae-4025-9b5c-0112d8e2b255 · outbound

This paper cites Batch normalization: accelerating deep network training by reducing internal covariate shift.

SchoenbAt: Rethinking Attention with Polynomial basis Batch normalization: accelerating deep network training by reducing internal covariate shift

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.403101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 73ec74d4-90d3-4530-943d-b4594800a385 · outbound

This paper cites Long range arena : A benchmark for efficient transformers.

SchoenbAt: Rethinking Attention with Polynomial basis Long range arena : A benchmark for efficient transformers

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.366251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a5b33cb3-ced1-423b-9b0f-9bf82bba3831 · outbound

This paper cites Maas, Raymond E.

SchoenbAt: Rethinking Attention with Polynomial basis Maas, Raymond E

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.335034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ed0ef5d4-f11e-451d-b594-23add7b2cb45 · outbound

This paper cites ListOps: A diagnostic dataset for latent tree learning.

SchoenbAt: Rethinking Attention with Polynomial basis ListOps: A diagnostic dataset for latent tree learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.309320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a744a1d-7629-4cdc-9ced-961216b679d2 · outbound

This paper cites Radev, Pradeep Muthukrishnan, and Vahed Qazvinian.

SchoenbAt: Rethinking Attention with Polynomial basis Radev, Pradeep Muthukrishnan, and Vahed Qazvinian

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.283544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6d62ec5d-cd2d-4515-979f-69680d114881 · outbound

This paper cites Houtkamp and P.

SchoenbAt: Rethinking Attention with Polynomial basis Houtkamp and P

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.259411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 933b85e6-ece4-419a-9494-3b6e15badf51 · outbound

This paper cites Learning multiple layers of features from tiny images.

SchoenbAt: Rethinking Attention with Polynomial basis Learning multiple layers of features from tiny images

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.323089Z

Source-reported events for the cited work

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Observation cae22f7c-2a14-444c-a1a5-56226a9a35aa · outbound

This paper cites Softmax-free linear transformers.International Journal of Computer Vision, 132(8):3355–3374, 2024.

SchoenbAt: Rethinking Attention with Polynomial basis Softmax-free linear transformers.International Journal of Computer Vision, 132(8):3355–3374, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.203414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3a22770e-3d54-4f08-9992-9c0133212f5d · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.

SchoenbAt: Rethinking Attention with Polynomial basis Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.170356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d5405bf4-3646-4eea-b227-23428297c88f · outbound

This paper cites CMAC neural network as an SVM with B-spline kernel functions.

SchoenbAt: Rethinking Attention with Polynomial basis CMAC neural network as an SVM with B-spline kernel functions

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.134581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 16836c42-bb3e-4a33-85d1-916c2c3fff3f · outbound

This paper cites Kernel methods for deep learning.

SchoenbAt: Rethinking Attention with Polynomial basis Kernel methods for deep learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.105125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2b852b2d-cfec-4ae0-bc8f-6241e7436953 · outbound

This paper cites Wavelet support vector machine.IEEE Transactions on Systems, Man, and Cybernetics, 34(1):34–39, 2004.

SchoenbAt: Rethinking Attention with Polynomial basis Wavelet support vector machine.IEEE Transactions on Systems, Man, and Cybernetics, 34(1):34–39, 2004

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.072825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dcd03bbd-97ff-4009-a762-7b8e0e9194f2 · outbound

This paper cites An explicit description of the reproducing kernel Hilbert spaces of Gaussian RBF kernels.IEEE Transactions on Information Theory, 52(10):4635–4643, 2006.

SchoenbAt: Rethinking Attention with Polynomial basis An explicit description of the reproducing kernel Hilbert spaces of Gaussian RBF kernels.IEEE Transactions on Information Theory, 52(10):4635–4643, 2006

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.043171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c64d06a9-45e5-41dd-88b2-00547512a989 · outbound

This paper cites Multi30K: Multilingual English-German image descriptions.

SchoenbAt: Rethinking Attention with Polynomial basis Multi30K: Multilingual English-German image descriptions

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:00.016651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3f64ced8-50ef-4a5a-ad75-1175f459fa7a · outbound

This paper cites Reformer: The efficient transformer.

SchoenbAt: Rethinking Attention with Polynomial basis Reformer: The efficient transformer

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:41:59.987430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cc81dffd-9133-419d-872b-27ad4a10607b · outbound

This paper cites Big bird: Transformers for longer sequences.

SchoenbAt: Rethinking Attention with Polynomial basis Big bird: Transformers for longer sequences

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:41:59.944776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f748f79e-0463-4ae3-8101-166f994583a0 · outbound

This paper cites cosFormer: Rethinking Softmax in Attention.

SchoenbAt: Rethinking Attention with Polynomial basis cosFormer: Rethinking Softmax in Attention

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T20:41:59.413605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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