Paper Citation Record · LEDGER

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING

As of 23 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 3 inbound Pith citation observations for arXiv:2502.02562.

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

pith.paper-citation-record.v1
2502.02562 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:50:03.404900Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T00:04:13.707931Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T00:08:43.783077Z

Reference resolution

71 of 71 outbound references displayed

verified exact2
verified fuzzy25
unresolved43
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01661b05-827f-406d-bb52-5d8bc21b21da · outbound

This paper cites Round and Round We Go! What makes Rotary Positional Encodings useful?.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Round and Round We Go! What makes Rotary Positional Encodings useful?

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.173708Z

Source-reported events for the cited work

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Observation 2903a036-e6c9-4cac-b44a-2a59805c6d55 · outbound

This paper cites PaliGemma: A versatile 3B VLM for transfer.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING PaliGemma: A versatile 3B VLM for transfer

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.178588Z

Source-reported events for the cited work

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Observation 5c1107d0-1b0d-4217-a906-3c0e9116bfb4 · outbound

This paper cites On computing givens rotations reliably and efficiently.ACM Trans.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING On computing givens rotations reliably and efficiently.ACM Trans

Reference 3

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Observation 1ad65f6d-be0b-4e21-973e-18d6c58b6039 · outbound

This paper cites Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols

Reference 4

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Source-reported events for the cited work

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Observation a45179ff-a548-46c8-bfcc-2f6311b025a4 · outbound

This paper cites SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities

Reference 5

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Source-reported events for the cited work

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Observation 38cbc3cc-6b24-47a4-b010-7708916f699e · outbound

This paper cites A simple and effective positional encoding for transformers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING A simple and effective positional encoding for transformers

Reference 6

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Source-reported events for the cited work

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Observation 4754ac83-8a2d-4dc8-9749-bf405a31106d · outbound

This paper cites Pali: A jointly- scaled multilingual language-image model, 2023.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Pali: A jointly- scaled multilingual language-image model, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.190813Z

Source-reported events for the cited work

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Observation 9392a143-8a7c-4baa-a004-98ee72b25db0 · outbound

This paper cites Ramadge, and Alexander Rudnicky.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Ramadge, and Alexander Rudnicky

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.181162Z

Source-reported events for the cited work

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Observation 30c98a46-964c-4974-adce-62a4f2950f02 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation 35daf527-9d9d-4b54-a808-29056ee9a268 · outbound

This paper cites Rethinking Attention with Performers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Rethinking Attention with Performers

Reference 10

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Observation e8d02b1c-d66f-4f8a-a8c6-5e358272300f · outbound

This paper cites From block- toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked transformers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING From block- toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked transformers

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.165870Z

Source-reported events for the cited work

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Observation f29f77db-481a-48dd-8200-f81c9e95e83c · outbound

This paper cites Abo: Dataset and benchmarks for real-world 3d object understanding.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Abo: Dataset and benchmarks for real-world 3d object understanding

Reference 12

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Observation b3bc62e0-7b25-4a2d-9d85-1c6911744ad2 · outbound

This paper cites Imagenet: A large-scale hierarchicalimagedatabase.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Imagenet: A large-scale hierarchicalimagedatabase

Reference 13

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Observation 9a96941b-6134-4f56-85fd-f299dbf6bb05 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 14

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Observation feb513a2-9f82-4353-8f49-d15c3fe5da49 · outbound

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

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING An image is worth 16x16 words: Transformers for image recognition at scale

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.150808Z

Source-reported events for the cited work

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Observation b797224c-680d-4f18-a2e6-256c7438b00f · outbound

This paper cites Google scanned objects: A high-quality dataset of 3d scanned household items.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Google scanned objects: A high-quality dataset of 3d scanned household items

Reference 16

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Source-reported events for the cited work

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Observation 60f5d1f4-486f-4371-96bf-84fdf152dc23 · outbound

This paper cites The Llama 3 Herd of Models.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING The Llama 3 Herd of Models

Reference 17

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Observation dd51dcfb-c7ea-4809-bb35-92645508b997 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Gemma: Open Models Based on Gemini Research and Technology

Reference 18

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Observation 95c8f39c-ca1e-485b-a7cb-8ad17fc5b9f4 · outbound

This paper cites Lvis: A dataset for large vocabulary instance seg- mentation.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Lvis: A dataset for large vocabulary instance seg- mentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.135380Z

Source-reported events for the cited work

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Observation c0fc717d-b1d6-4c5b-a74b-48829c9e0ed0 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Springer, 2013

Reference 20

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Source-reported events for the cited work

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Observation d83b7b4f-672b-4ff4-acae-553297a11c95 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Gaussian Error Linear Units (GELUs)

Reference 21

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Source-reported events for the cited work

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Observation e036886a-5f63-4877-a78f-481dfcfd678a · outbound

This paper cites Rotary position embedding for vision transformer.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Rotary position embedding for vision transformer

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.116020Z

Source-reported events for the cited work

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Observation 5dddd6d1-960f-4a44-9cd4-db1da22ba50c · outbound

This paper cites Integrating Generic Sensor Fusion Algorithms with Sound State Representations through Encapsulation of Manifolds.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Integrating Generic Sensor Fusion Algorithms with Sound State Representations through Encapsulation of Manifolds

Reference 23

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Observation db27b884-be0f-406c-8d19-ab4b53f01f15 · outbound

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

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 24

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Source-reported events for the cited work

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Observation 4828a124-57ec-41c0-b3c2-954cfc819a9a · outbound

This paper cites The impact of positional encoding on length generalization in transformers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING The impact of positional encoding on length generalization in transformers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.100569Z

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Observation d72693a8-51dc-4418-9532-f45083b5c040 · outbound

This paper cites SHAPE: Shifted absolute position embedding for transformers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING SHAPE: Shifted absolute position embedding for transformers

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.091625Z

Source-reported events for the cited work

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Observation dbca497e-de5d-4419-9a51-296e25b08732 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:04.082776Z

Source-reported events for the cited work

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Observation 3c7cc16f-8254-436c-97dc-378d7ce23ae3 · outbound

This paper cites Functional interpolation for relative positions improves long context transformers.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Functional interpolation for relative positions improves long context transformers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.073695Z

Source-reported events for the cited work

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Observation 44ed6f5a-6f18-4e02-8df3-10a9798d0f90 · outbound

This paper cites Microsoft coco: Common objects in context.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Microsoft coco: Common objects in context

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.064400Z

Source-reported events for the cited work

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Observation 3cd0e8d4-9c06-4c24-bf57-dc1f16f9a8c9 · outbound

This paper cites Dhillon, and Cho-Jui Hsieh.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Dhillon, and Cho-Jui Hsieh

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.055219Z

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Observation c3322365-2acd-4f33-8a6e-34e352fb04d7 · outbound

This paper cites Stable, fast and accurate: Kernelized attention with relative positional encoding.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Stable, fast and accurate: Kernelized attention with relative positional encoding

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.045944Z

Source-reported events for the cited work

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Observation 06170eb0-3fdc-4c00-8010-862a64278fcb · outbound

This paper cites Simple open-vocabulary object detection with vision transformers.ECCV, 2022.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Simple open-vocabulary object detection with vision transformers.ECCV, 2022

Reference 32

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Observation b44e797d-4fe2-4681-ac1e-48077e021c6d · outbound

This paper cites LieRE: Lie Rotational Positional Encodings.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING LieRE: Lie Rotational Positional Encodings

Reference 33

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Observation ea2fd393-80ef-4544-b9f3-b3ac535f57ec · outbound

This paper cites Smith, and Mike Lewis.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Smith, and Mike Lewis

Reference 34

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Source-reported events for the cited work

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Observation 83be2e02-fa45-4f0c-8c4b-57992819da26 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Learning transferable visual models from natural language supervision

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:04.017222Z

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Observation aae62530-0b05-4ec9-ac36-9cc850603448 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:04.007516Z

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Observation 224c513e-eded-4c0d-8a51-4b18cad255ca · outbound

This paper cites Linear Transformer Topological Masking with Graph Random Features.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Linear Transformer Topological Masking with Graph Random Features

Reference 37

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Observation c633c853-5200-4cd1-82a3-c9e37c65ce66 · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Code Llama: Open Foundation Models for Code

Reference 38

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Observation dea00aa8-5534-4ffc-b7f4-0e518a8527ad · outbound

This paper cites Recognition of distorted patterns by invariance kernels.Pattern Recognition, 24(10):959–967, 1991.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Recognition of distorted patterns by invariance kernels.Pattern Recognition, 24(10):959–967, 1991

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.997419Z

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Observation 69b32438-0186-4d8b-a79a-f53fc344056c · outbound

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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.987577Z

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Observation 4eaf99f7-8c37-4514-930e-d7e335e90efd · outbound

This paper cites Self-Attention with Relative Position Representations.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Self-Attention with Relative Position Representations

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.312598Z

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Observation d1b94f03-e912-47ca-a458-91242df1b879 · outbound

This paper cites Revisiting energy based models as policies: Ranking noise contrastive estimation and interpolating energy models.Transactions on Machine Learning Research, 2024.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Revisiting energy based models as policies: Ranking noise contrastive estimation and interpolating energy models.Transactions on Machine Learning Research, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.978239Z

Source-reported events for the cited work

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Observation dec3afea-03b7-41e9-8a2d-ce33dbdf664a · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.319128Z

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Observation 61da5423-5193-48ca-a002-8133a2e06cb0 · outbound

This paper cites Equivariant transformer networks.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Equivariant transformer networks

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.962470Z

Source-reported events for the cited work

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Observation 5eb222d8-5662-4c41-b37e-208ff861857b · outbound

This paper cites Early or late fusion matters: Efficient rgb-d fusion in vision transformers for 3d object recognition.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Early or late fusion matters: Efficient rgb-d fusion in vision transformers for 3d object recognition

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.952946Z

Source-reported events for the cited work

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Observation a1b73642-818e-4077-9bc7-cca64b6b83b5 · outbound

This paper cites Divya Udayan, Veerababu Addanki, Sathvik Durgapu, Dhanvanth Reddy Yerramreddy, and Dorasanaiah Kolla.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Divya Udayan, Veerababu Addanki, Sathvik Durgapu, Dhanvanth Reddy Yerramreddy, and Dorasanaiah Kolla

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.328237Z

Source-reported events for the cited work

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Observation 00314a30-8e14-4af5-acee-7023dfcc0e60 · outbound

This paper cites Unity, 2023.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unity, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.943762Z

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Observation 8c1d6b4c-cda6-4816-94d6-57811b2adbe7 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.934318Z

Source-reported events for the cited work

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Observation 7af7f83b-a9f1-4b40-94c3-8d97d0802a2c · outbound

This paper cites On position embeddings in BERT.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING On position embeddings in BERT

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.924965Z

Source-reported events for the cited work

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Observation deef4fd9-70e1-4e17-9a3e-b4ff77da508b · outbound

This paper cites Effective Long-Context Scaling of Foundation Models.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Effective Long-Context Scaling of Foundation Models

Reference 50

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Source-reported events for the cited work

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Observation 5c02768f-4688-4434-8e8e-73af0b38d53f · outbound

This paper cites Depth Anything V2.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Depth Anything V2

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.344231Z

Source-reported events for the cited work

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Observation dab94acc-8b9c-4fa1-9a64-df9800c161cb · outbound

This paper cites Sigmoid Loss for Language Image Pre-Training.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Sigmoid Loss for Language Image Pre-Training

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.347634Z

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Unavailable: canonical work link unavailable.

Observation 78e47b44-9be6-48e8-b381-829f300d29c2 · outbound

This paper cites Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.351225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fe7f2c3-bb5b-4f39-8e37-8b1368925532 · outbound

This paper cites ALOHA Unleashed: A Simple Recipe for Robot Dexterity.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING ALOHA Unleashed: A Simple Recipe for Robot Dexterity

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.358012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95cd4f16-dd51-4f35-8754-b773f4aa3179 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.915945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bc0985a7-b5b0-4340-87dd-6a995e52304d · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.907363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2048b349-02d3-443e-9ad7-3a96ad1ac067 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.898469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3d390c4e-d7f8-43fc-8a8d-16b1ff13fbd4 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.889703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 024f88b0-cef5-43b9-89e3-d903663ff466 · outbound

This paper cites MultiTask aggregates results of all of the above tasks.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING MultiTask aggregates results of all of the above tasks

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.881052Z

Source-reported events for the cited work

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Observation 7e1974ce-2620-4097-b1e7-8d8375899601 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.872094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b122169d-40a3-4199-a452-e90562779380 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.863398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 76e4ae5a-ffa5-4bfa-855d-55d7886d1f4d · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.853791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ca7350f5-7b11-4f6f-b889-ab1db33fd890 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.845253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ac8f0c27-1312-494c-a4a5-8a9097a906aa · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.836345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fb5a746f-ee33-4705-892a-3919d0d7f50f · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.826548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7b0df1de-41dc-411e-8046-44bbce4edce8 · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.817226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 71eec2c1-7364-4b43-8eaa-6e7cfe100abf · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.807848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7b90a313-72a4-4655-81f9-2354b0b7b73d · outbound

This paper cites an unresolved cited work.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:50:03.798723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bb7c1582-560f-4c01-a0ac-07f46aa36b03 · outbound

This paper cites See: Fig.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING See: Fig

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:50:03.789166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 23445b44-35a4-41e1-ba3b-a89c18ea436b · outbound

This paper cites doi: 10.18653/v1/2021.emnlp-main.266.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING doi: 10.18653/v1/2021.emnlp-main.266

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.262389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 567357f9-acd8-4295-ad04-922e637d90e9 · outbound

This paper cites Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding.

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T11:50:03.354747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation cc58e1d0-925c-4e5b-b85e-b14dff6834c3 · inbound

Group Representational Position Encoding cites this paper.

Group Representational Position Encoding Learning the RoPEs: Better 2D and 3D Position Encodings with STRING

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:08:43.785650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ee44d256-fdd5-4292-9a30-5b5d2139851e · inbound

CLAMP: Contrastive Learning for 3D Multi-View Action-Conditioned Robotic Manipulation Pretraining cites this paper.

CLAMP: Contrastive Learning for 3D Multi-View Action-Conditioned Robotic Manipulation Pretraining Learning the RoPEs: Better 2D and 3D Position Encodings with STRING

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:27:36.885411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ee280d7c-7ee5-410c-984d-9481b1a87167 · inbound

Elastic Attention Cores for Scalable Vision Transformers cites this paper.

Elastic Attention Cores for Scalable Vision Transformers Learning the RoPEs: Better 2D and 3D Position Encodings with STRING

Reference 157

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:07:22.586582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.