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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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
  • malformed identifier1
  • metadata mismatch0

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.173708Z digest=sha256:319227021cbc86ef7fe1f8a8f95a6535cada8e6dc7ce1ecab3f0f7059260a9e6

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

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.178588Z digest=sha256:77fb47312424497984babb184dae04b7faacfa0f419e9fb94c33b05c4269caba

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.186231Z digest=sha256:0f3c65a69fbc6de5ba484ff129de98ec3854af32ff42060cd701459b2eb6deb1

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.189919Z digest=sha256:5dd783a46223bb697b2b21767d24d8be197256f2c1feb405377f42ecda2a9eb0

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

Unavailable: canonical work link unavailable.

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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

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

Source-reported events for the cited work

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

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Observation 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

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

Source-reported events for the cited work

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

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

This paper cites an unresolved cited work.

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.203875Z digest=sha256:4fbf5edddfd6e1048539a2431b6fd5e870c320b781dc1fedf22ba731f9f8e67d

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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source=pdf_text observed=2026-08-09T11:50:03.207085Z digest=sha256:bccbd712647bb7bee62ef597d59750be28179c721fed32835f05a425bd341b3a

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

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

Source-reported events for the cited work

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

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Observation 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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no resolver link, observed 2026-08-09T11:50:03.214297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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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verified exact
arxiv_id_nonexistent, observed 2026-08-09T11:50:03.667714Z

Source-reported events for the cited work

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

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

This paper cites an unresolved cited work.

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

Reference 14

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malformed identifier
no resolver link, observed 2026-08-09T11:50:03.220727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.220727Z digest=sha256:f908a1f2504acf237ba0b0835b8756317f70fc111f73fdf96599a0c1e19ef374

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

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

Source-reported events for the cited work

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

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Observation 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

Unavailable: canonical work link unavailable.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.233540Z digest=sha256:ab5c30308a97d672016fb16eccad6f23fe8e7d549fc6a12c04f59696e736e01b

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

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.236772Z digest=sha256:1b6d5f89b1ab10c324423e2f6f4f013c095d7629a3f79ca81157b349a138cc0d

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

This paper cites Springer, 2013.

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

Reference 20

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raw_fallback, observed 2026-08-09T11:50:04.125845Z

Source-reported events for the cited work

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

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Observation 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

Unavailable: canonical work link unavailable.

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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

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

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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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local_arxiv, observed 2026-08-09T11:50:03.605769Z

Source-reported events for the cited work

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

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Observation 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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.253000Z digest=sha256:eed48cd3ddf95141327c1e7dc0c8665ca9242a8b479c5467f3bf5fd8be160d9e

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

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

Source-reported events for the cited work

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

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Observation 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

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

Source-reported events for the cited work

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

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

This paper cites an unresolved cited work.

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

Reference 27

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

Source-reported events for the cited work

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

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Observation 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

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

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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

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.271932Z digest=sha256:712d265e7a783e98fcaf6fa7c8f530a649f4156113c5bcd36d099b52fca8229d

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

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

Source-reported events for the cited work

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

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Observation 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

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

Source-reported events for the cited work

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

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Observation 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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raw_fallback, observed 2026-08-09T11:50:04.036726Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.284169Z digest=sha256:e80845e764caa9ce13398e2fe7425f7d32641c2e16a25c19c24c51891b38b873

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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no resolver link, observed 2026-08-09T11:50:03.287163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.287163Z digest=sha256:e7b39981ad818932c25b6579892ac1fe3f476caeb9a003cbc46fbec5b1f2a3a3

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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verified fuzzy
raw_fallback, observed 2026-08-09T11:50:04.026940Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.290518Z digest=sha256:c2be6f9eac6a8d1aeda05ff58105aae99528af51bd2d660af5a052d749f3efee

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

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.293332Z digest=sha256:fb625f668b303c26cea286fb37f20294fa2f4a6bf3a56cea9d7a72809d7fc5fb

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

This paper cites an unresolved cited work.

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.296395Z digest=sha256:e2a134a6b2cd7573831b8b3d79ce2fb91d08d92822c062140bf6982107d0e7ae

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

Resolution
unresolved
no resolver link, observed 2026-08-09T11:50:03.299389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.299389Z digest=sha256:a23c15e779f79d0e9610ca76361664cff855a51d8ff8419571ff5ca9ce33a87c

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

This paper cites Code Llama: Open Foundation Models for Code.

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

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-09T11:50:03.302995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.302995Z digest=sha256:4c1ec81a94122e2864601c25bc0b538d3d501331bb6c44451ed4f8ddf79f267a

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.306352Z digest=sha256:372496d8366d192ba58ba013a03f3c357ee4165c4bae86b648e55cb35b88a1c2

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

This paper cites an unresolved cited work.

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.309418Z digest=sha256:ecc4ed6258753b533d5add15677ffac299094eb17807da9772118f1a46793750

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.312598Z digest=sha256:1856ebe93569986cb0447330e0460586775285da5de7760798eb3799e43926fa

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

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

source=pdf_text observed=2026-08-09T11:50:03.316236Z digest=sha256:1f60ee24d6e26e6420fcbfd13005503612dd94a14d4fc6b0c9152b8df7a1c619

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.319128Z digest=sha256:9ae8943a7d8b6aee0f33703015e569168284ff008abafb8b06fd61183db7ae7c

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

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

source=pdf_text observed=2026-08-09T11:50:03.322135Z digest=sha256:17641d7880867764597d2589dd59546e7674690fcffccab027cc185b70be6c31

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

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

source=pdf_text observed=2026-08-09T11:50:03.325224Z digest=sha256:eb8ea51b8addd9b3ef663d5b3657afee4fad5f5396202b281ce71cd56c3a94f4

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.328237Z digest=sha256:cfaee27d58f90516084137696e8688fc3c484562395392f7452d4ce23669d70a

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T11:50:03.331260Z digest=sha256:c68022d1143c3eb881b0bad1a805e9450d0cbb1a3fe0c216922f2eac71087afa

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

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

source=pdf_text observed=2026-08-09T11:50:03.334292Z digest=sha256:a39d67cdf647da8b7f097bbf13b21397a02e08fb5ec52749cd08b175b9bae0ac

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

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

source=pdf_text observed=2026-08-09T11:50:03.337518Z digest=sha256:097828ef5ec72c20973f14f0442b15d07a409204364b12a5c80aeff24d580cc3

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

Resolution
unresolved
no resolver link, observed 2026-08-09T11:50:03.340792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.340792Z digest=sha256:6fda4d1d35b1a82ff7e06b16653f831aad2b29444f42fdc04368596f151e0fdf

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.344231Z digest=sha256:e536d17a75de15c7c3f154de7008a76bc72a84a45f21cfecec070918e604ea5c

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:50:03.347634Z digest=sha256:67f50e222bc917f95ec9ada715fd1bf7baf83631f5e9c5bd239f122c0ff31722

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.

source=pdf_text observed=2026-08-09T11:50:03.351225Z digest=sha256:063c91b68558ab17d829a98a174b0d039f950e9ce0311ee6b4a11afd170d8f1a

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.

source=pdf_text observed=2026-08-09T11:50:03.358012Z digest=sha256:b1ac7f97c54e25d94a6b92f0fc92caa5a2860b57296fb262cc3996ab9f0634ad

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.361877Z digest=sha256:6c915635d2b46e6d9f2f1d056d8c50fda20107e3972b0fc6916ec5a783c76374

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.365034Z digest=sha256:bc5938910e71f74e1bf6e6c2a9c87a023a8e41362962fbd492fc6388906f6075

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.368346Z digest=sha256:74f9f9c0743046c583920997d865420d1ac6c58af7ea8075875de5352af94c81

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.371431Z digest=sha256:53f7f674de3159c1164cb7a92d684092d9a45275b23759b4d2f9b7c53ab9d7f2

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

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

source=pdf_text observed=2026-08-09T11:50:03.374386Z digest=sha256:c4fe37e776c25dd9c8f8fb70c0a49a241af277edc0269c9f660f5e2ade2ed50b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.377349Z digest=sha256:e57c10202703e85d3d7da04cbca4f10bb4bce65390667b8659476c1ab81ded7a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.380313Z digest=sha256:cc486c009efb0668279d3a44e5487ce265648425ac6ffa6a15f01fbccf867f3a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.383222Z digest=sha256:7b0793d793ae7fecd87c86cb30d37d4c736e6b934ac64f670d2b86c3834efaf4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.386083Z digest=sha256:f60c968345b235dc1aa459b0eae96eb60a2b0a5066333eb96fbcf8430029d4c4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.389111Z digest=sha256:e81f769cf75cafc4a9e898b72d5b5dbcafab41dffa6899a6f089cba4950706db

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.392494Z digest=sha256:bf9c9b059a4f22a059f3a77446f04ebb30cb1d4292f88a8030e3f228c5d4bdc0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.395549Z digest=sha256:52710b6eae4793cd0cd2a7f1b94104e3756fc91868437dc294695f1d7b7dbe33

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.398572Z digest=sha256:6d5e9d7522c178f1d5c9f6b54110cf8b1726829b0fd8ea84a44b2d0935a62d6d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.401809Z digest=sha256:cec7021d259595fdbda6a59fd6b650daf5555910086a9fadda565400092bbd65

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T11:50:03.404900Z digest=sha256:f3da3621d9ae14902d0da8592c506b71b06878738652e4364e02959fe0a260fc

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.

source=pdf_text observed=2026-08-09T11:50:03.262389Z digest=sha256:9a54572b018dadadaa6f7956a98db7242c519ce00f11c1a141dda4dd5bcb85c2

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.

source=pdf_text observed=2026-08-09T11:50:03.354747Z digest=sha256:e7904c099f8e4159a343802f04a51f1d5985e2c273a1337eee7e588b2065257b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T00:04:13.707931Z digest=sha256:41dfa665b24f5b2475263fcc03ad3b7de9ffc010c94a7f8c529da567dca7eeb6

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T08:24:44.943709Z digest=sha256:333bd187118430225385f81bdf1b2a29dbb4bb472f565f22b688bee17a8b99ac

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T06:02:40.158866Z digest=sha256:c0559f2dd8bb93bada62ee86c537a74a0a1013607c7c951613af2227dfec06a3