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Paper Citation Record · LEDGER

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 3 inbound Pith citation observations for arXiv:2506.03737.

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

pith.paper-citation-record.v1
2506.03737 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:03:17.525121Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:25:17.276223Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T19:01:46.040401Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact4
  • verified fuzzy17
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 12b9b99b-62d6-4100-9383-00d70f3c1b43 · outbound

This paper cites Comput- ing the matrix exponential with an optimized taylor polyno- mial approximation.Mathematics, 7:1174, 2019.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Comput- ing the matrix exponential with an optimized taylor polyno- mial approximation.Mathematics, 7:1174, 2019

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:19.293665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f21d0dd8-8adf-41db-8eb7-d0748ac59dfa · outbound

This paper cites Language Models are Few-Shot Learners.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Language Models are Few-Shot Learners

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:15.853510Z digest=sha256:3b20fa579ec80bc1efc2db155c4261e055dcd0755a297976d77b155238ffaca6

Observation 54f351eb-7ed1-4bac-a069-5300fd9a42ee · outbound

This paper cites GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization

Reference 3

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source=pdf_text observed=2026-08-07T11:03:15.864347Z digest=sha256:24859610c5888ff317cbb747a3dcbdbc69e4579bda1f85f06b7ad8bf8607d364

Observation 973f2a20-f9e5-48fb-9493-f8363e09a88c · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, march 2023.URL https://lmsys.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, march 2023.URL https://lmsys

Reference 4

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source=pdf_text observed=2026-08-07T11:03:15.880197Z digest=sha256:9e838804735598d857a114b5feba68f911650ba55257e96e209c59515e266379

Observation 72e64d48-7c70-4457-a78b-d1a2a262cb01 · outbound

This paper cites Li, and Li Fei-Fei.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Li, and Li Fei-Fei

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-07T11:03:19.222656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:15.895061Z digest=sha256:ad050ec48de6c81a2bd4f65f875f28c46ffa115c8a6a5fecff8c783df31392fd

Observation 4f591d58-d4a5-43b9-b8db-adf6dfd87534 · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:15.926770Z digest=sha256:f0db61dd396931c02e7ce28dbfa8bdf69791c061d3b30e39246ccf95bbf12502

Observation eeb28c5c-511f-46ea-a8ad-048d451bafd3 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

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source=pdf_text observed=2026-08-07T11:03:16.645130Z digest=sha256:7c2aac978d5813ad62b8dbdbe0b6cbff5016172af3136a13d8cb006cf94a40b7

Observation 75268850-cf34-4eb7-b6ab-624ee0ab0432 · outbound

This paper cites Eva-02: A visual representation for neon genesis.Image and Vision Computing, 149:105171,.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Eva-02: A visual representation for neon genesis.Image and Vision Computing, 149:105171,

Reference 8

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source=pdf_text observed=2026-08-07T11:03:17.068841Z digest=sha256:dce8d9bcad8fbdb9ba4b0120bde7a0b129778bfdf61fbcd342ca52cc463128c5

Observation 2d02d34d-c12b-49f5-8b07-bb3afb82c252 · outbound

This paper cites an unresolved cited work.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9ab59422-6a14-4bab-95c5-016a912a00f5 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 10

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source=pdf_text observed=2026-08-07T11:03:17.091547Z digest=sha256:3255ec88eb66f5d731dd37a00e9a321046996b1c4bdc2a14b9b877d90f224d50

Observation 7aa67cbb-8a47-45d7-80e5-9e01c8309ec5 · outbound

This paper cites an unresolved cited work.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Unresolved cited work

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.096594Z digest=sha256:49c4b6272f59b02ae9d7738b3e323b7ab73eadc64a81c7e5ff749e9cdbf8e032

Observation 80a01eb5-f9fa-4f1f-bd53-416ef87516c5 · outbound

This paper cites Rotary Position Embedding for Vision Transformer.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Rotary Position Embedding for Vision Transformer

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.114723Z digest=sha256:7e4ce03fe0900f4b924165fa1a7e1f5dee7fbf58eae12022b798e18bdee99050

Observation a6069d5b-65b8-4d0c-a349-962121214cc5 · outbound

This paper cites Translational Equivariance in Kernelizable Attention.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Translational Equivariance in Kernelizable Attention

Reference 13

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local_arxiv, observed 2026-08-07T11:03:18.272043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.123092Z digest=sha256:a1af7f70b0d996ac6f891deb0e1a1fc1f75e3cc63c70bc4d731df7fc72751cee

Observation 37ced72e-af0c-4b46-b036-1c270c231a8f · outbound

This paper cites The impact of positional encoding on length generalization in transform- ers.Advances in Neural Information Processing Systems, 36: 24892–24928, 2023.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices The impact of positional encoding on length generalization in transform- ers.Advances in Neural Information Processing Systems, 36: 24892–24928, 2023

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T11:03:19.077543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.140945Z digest=sha256:5ee1374780c62a877ab98268dec71a99bdd82c6e7fcf5bb64433ca21a3aba1f9

Observation e93ae559-9002-4cbb-9585-eab52add3cba · outbound

This paper cites Autowebglm: A large language model-based web navigating agent.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Autowebglm: A large language model-based web navigating agent

Reference 15

Resolution
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raw_fallback, observed 2026-08-07T11:03:19.037900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.159702Z digest=sha256:f8c5cd7d3fd92da9f878db82d779fb6eecbb69e763952449ffaafe9d82a47c12

Observation 396438cd-7478-4801-ac34-1f5cec8d7300 · outbound

This paper cites LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding

Reference 16

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source=pdf_text observed=2026-08-07T11:03:17.170264Z digest=sha256:88366f1c8826356b792beb43cb02083108507680cc111c817bb7773acbada743

Observation fb6adad4-5e37-470e-ad3e-679232b46e5b · outbound

This paper cites Microsoft COCO: Common Objects in Context.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Microsoft COCO: Common Objects in Context

Reference 17

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no resolver link, observed 2026-08-07T11:03:17.176983Z

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source=pdf_text observed=2026-08-07T11:03:17.176983Z digest=sha256:f37f9f5a09ae6219e6c3686b0c5532f46ea72ccca88be83c04643def51c46437

Observation 0bb945e5-e7b7-450c-8dc8-1881d1e12b68 · outbound

This paper cites We- bglm: towards an efficient web-enhanced question answer- ing system with human preferences.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices We- bglm: towards an efficient web-enhanced question answer- ing system with human preferences

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:19.002699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.186414Z digest=sha256:59450b8f68f3dc47da913c5ec5768c8f95f2a63fc05b753581df13a6c62af7e0

Observation 27f4e856-8636-45b1-87f4-d64fe53206b2 · outbound

This paper cites Agentbench: Evaluating llms as agents.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Agentbench: Evaluating llms as agents

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.979574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.198567Z digest=sha256:40b11559a90f4d266af5c0ab6df762e4ec5fbf2f176d33689838501e3f8123de

Observation 914a22aa-f76d-4424-a2ed-249999070843 · outbound

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

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Swin transformer: Hierarchical vision transformer using shifted windows

Reference 20

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source=pdf_text observed=2026-08-07T11:03:17.212463Z digest=sha256:ae7012eada6f78b87567efda119f5d48fc967c674853dd0341f4e9def0da919c

Observation 65c4ae84-fbc8-4a0f-bb90-30933aff2108 · outbound

This paper cites Relative positional encoding for transformers with linear complexity.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Relative positional encoding for transformers with linear complexity

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.905658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.221236Z digest=sha256:66a8b72a149185f578890fc6f871bf8c86db394b503cce7512eea94daf8967f7

Observation ee606c24-3d76-4b9a-96d9-88c5f9e152f6 · outbound

This paper cites Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action

Reference 22

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source=pdf_text observed=2026-08-07T11:03:17.233095Z digest=sha256:07ea6a7ea0f2e9336c42ea132fdbcd32f543e13e2d43de3390d3744ae7db6cbb

Observation cd92e9f9-f723-45f6-8cee-fec3f7c4d4a6 · outbound

This paper cites LieRE: Lie Rotational Positional Encodings.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices LieRE: Lie Rotational Positional Encodings

Reference 23

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source=pdf_text observed=2026-08-07T11:03:17.242892Z digest=sha256:b972c5ca64d04a426b4152adbca3191c0db7c7d4e50ca0e13dd182e2ac4dae29

Observation 2b158ff4-da6d-482f-8388-d91140e1f7ef · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 24

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source=pdf_text observed=2026-08-07T11:03:17.265819Z digest=sha256:0cd66903a5f3dbfcc2444d6109c4797874cc0d497781473c283dfdec9857f3dc

Observation 7e4a1f5a-5e7e-4404-a299-dd080ca10a24 · outbound

This paper cites Improving language understanding by generative pre-training.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Improving language understanding by generative pre-training

Reference 25

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raw_fallback, observed 2026-08-07T11:03:18.852726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.278863Z digest=sha256:a811705e12cf8f29a1388e42de9cd88830bff26ffeb9118d6f0185b085e939e8

Observation 9fa1f528-e8fa-4a16-a27b-10baf367e29a · outbound

This paper cites Language models are unsu- pervised multitask learners.OpenAI blog, 1(8):9, 2019.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Language models are unsu- pervised multitask learners.OpenAI blog, 1(8):9, 2019

Reference 26

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source=pdf_text observed=2026-08-07T11:03:17.307518Z digest=sha256:b8e5c501335ef921486624d7a3ad3f22af31526cf08990aa1a87f58e5dce449c

Observation 4d530d71-3b63-48b0-814b-d9d008faebdc · outbound

This paper cites Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and I.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and I

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.811054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.324254Z digest=sha256:35132c2bbc035e4e0005a2fbb60b0fb7380d66b77d25ce487c999247c25da976

Observation bc43e7a5-8130-4aed-9193-0b9ef102d9ea · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

Reference 29

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source=pdf_text observed=2026-08-07T11:03:17.373478Z digest=sha256:ae754c9bd2d22c0200e1ce7f44696c3538665c088a6a0f559248e873289e70d5

Observation 9409c54a-2e38-4864-b09c-766b60021958 · outbound

This paper cites Self-Attention with Relative Position Representations.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Self-Attention with Relative Position Representations

Reference 30

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source=pdf_text observed=2026-08-07T11:03:17.391577Z digest=sha256:b15dbd0a785ba4e83c26cafaf92ea887f91fc4e6eba6bb4bf9b8ec1f2c29fbae

Observation 7b9ff182-186a-4f52-85d3-f1f1c4d84c68 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.412046Z digest=sha256:9180797a8b928ec79558465e9ce68ba22deca9c1decf820a235f6ce2342e4d19

Observation b5a40937-9aad-4a59-ae69-8e59be06edca · outbound

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

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063,

Reference 32

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no resolver link, observed 2026-08-07T11:03:17.417243Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.417243Z digest=sha256:6c7515ba10072e3f61ecd1e495331456a55c330d0ce89406a4bb1723e0f524d6

Observation a3808efb-820c-48a6-bf52-525200d2e19b · outbound

This paper cites End- to-end memory networks.Advances in neural information processing systems, 28, 2015.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices End- to-end memory networks.Advances in neural information processing systems, 28, 2015

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.753153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.422077Z digest=sha256:5345db9be28b9e7de6278ddb08f53602a1f2410d1fd97ab08e37108cf1c5164a

Observation 987513f9-9161-475e-83af-e139f4801e77 · outbound

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

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices LLaMA: Open and Efficient Foundation Language Models

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.430858Z digest=sha256:2ffab59fea0a1e6ac2b8a7bba7020c4f2bd8416e3de34465fadeb559169aed3f

Observation 0b7d1bfe-932a-47fb-970f-e1d69be8e8b1 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:17.438302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.438302Z digest=sha256:13ef010f57c737439f455564cb1471db579dc4cc28b63ce688c3c536e80cf0eb

Observation 6e585a2e-72cb-4904-a0d0-b4f635d6bfd7 · outbound

This paper cites Rethinking and improving relative posi- tion encoding for vision transformer.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Rethinking and improving relative posi- tion encoding for vision transformer

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.691105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.446303Z digest=sha256:ce16677e5aa9869b2508486b2f91f654676c062a1b5e83ad4c1db05bd01c1372

Observation 867e204b-8aee-4818-9758-af6267e5ece1 · outbound

This paper cites Vit-comer: Vision transformer with convolu- tional multi-scale feature interaction for dense predictions.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Vit-comer: Vision transformer with convolu- tional multi-scale feature interaction for dense predictions

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.643149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.452943Z digest=sha256:7c4a7b84110294ccecdc6bed90b4e69c1c966360ca4469324b780071ac92743a

Observation a3ed2881-9cd1-469e-bad0-9fa6ec7dcede · outbound

This paper cites Weakly Supervised Temporal Action Localization via Dual-Prior Collaborative Learning Guided by Multimodal Large Language Models.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Weakly Supervised Temporal Action Localization via Dual-Prior Collaborative Learning Guided by Multimodal Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:17.468809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.468809Z digest=sha256:efa8eed2da001f9304da1f4b8275f28cf7bc535ef5ffd9e89968f4660923210a

Observation 8dfc17c9-aa11-4056-b3a8-39dd66787d8d · outbound

This paper cites Distilling semantic priors from sam to efficient image restoration models.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Distilling semantic priors from sam to efficient image restoration models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.598357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.478606Z digest=sha256:09cae98b3edaf3f9b2223047392936adfcd661b06e1dca0b8845f03055cad406

Observation 33d202d0-0f13-4dca-8f77-946568347456 · outbound

This paper cites IMDPrompter: Adapting SAM to image manipulation detection by cross-view automated prompt learning.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices IMDPrompter: Adapting SAM to image manipulation detection by cross-view automated prompt learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.571961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.486393Z digest=sha256:dce1db08eff0088ae89d8707193b655328012f0bba48efbef4ffa351ed0b5c32

Observation 3f4b02f4-d560-4eb3-8829-b9fd882d893d · outbound

This paper cites Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:03:17.916086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.493114Z digest=sha256:bb7672066049d24412f25e3a3e6902caa4114f82505bc150cd93be7eadb3974e

Observation 5e0ad6eb-47e9-43e2-a190-17c800383e2c · outbound

This paper cites (13) SubstitutingA,BwithAx,By, we obtain: eAx+By =e AxeBy.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices (13) SubstitutingA,BwithAx,By, we obtain: eAx+By =e AxeBy

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.553832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.501418Z digest=sha256:97c3fb8e09457877fe67e87ff1b4ab0e2d98bb9b8318d0150476db7b7dc31ac3

Observation be062033-7cca-40b9-8fa7-dea9c51e3c11 · outbound

This paper cites (16) Lett 2f(t)be the difference between the two expressions above.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices (16) Lett 2f(t)be the difference between the two expressions above

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.521369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.508488Z digest=sha256:b7d130bd6613677e189f6cc8c3012e0949e20bc635b2ac7bb4039dc267f1bcce

Observation 2f62e89a-d5fd-4661-9ac9-4fc478773182 · outbound

This paper cites (21) SinceA 1,A 2,.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices (21) SinceA 1,A 2,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:18.501800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.514067Z digest=sha256:590b3d7f74de3cb439cbe907af6c648bf417b95abff9c6d9aedda8de29d6b599

Observation 9f41fc52-2bd9-49d3-bc50-4a9f21bd562f · outbound

This paper cites Then: eA1x1 eA2x2 · · ·eAkxk =e A1x1+A2x2+···+Akxk , (23) implying thatA 1,A 2,.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices Then: eA1x1 eA2x2 · · ·eAkxk =e A1x1+A2x2+···+Akxk , (23) implying thatA 1,A 2,

Reference 45

Resolution
verified exact
raw_fallback, observed 2026-08-07T11:03:17.878085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.519444Z digest=sha256:dd40adbc431c8a914d97bf0fcbae9eff32b2583b09d45e2db3a9365c1fe4f460

Observation d8d74c10-ac19-49e6-b3d5-6203923fe5b1 · outbound

This paper cites We obtain: f(x 1 +y 1, x2 +y 2,.

ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices We obtain: f(x 1 +y 1, x2 +y 2,

Reference 46

Resolution
verified exact
raw_fallback, observed 2026-08-07T11:03:17.754065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:03:17.525121Z digest=sha256:834325a75d05cf8850940618b4c3258d6cb550ed54c047a4ab276bf46a49935d

Pith citing papers

Observation abd953b8-d01c-431c-8fdc-9a68f4ec2e8b · inbound

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation cites this paper.

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:01:46.043262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-18T18:56:48.722344Z digest=sha256:75bd23994600475522942f344198120436e58565011b12d40d74f4bd6bc3864b

Observation f28e1c19-4032-4735-8d71-97edac601110 · inbound

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation cites this paper.

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-05T10:25:17.276223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T10:25:17.276223Z digest=sha256:afcfac695bc46439337e004ef5c3b97bf1cefe0860546034c073adeca64b6c3b

Observation 6683ef19-794a-4d4f-b703-e82680c15c9c · inbound

The Transformer as a Polar State Estimator cites this paper.

The Transformer as a Polar State Estimator ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

Reference 173

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T02:17:07.510187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T00:58:28.483037Z digest=sha256:b988b41ab519fd754c94796b7ba40166f7d3c6fe97e7c2db68a78e35a8949445