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Paper Citation Record · LEDGER

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

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 5 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 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:54:26.642378Z

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

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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 2026-08-18T06:34:40.430872+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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:15.853510Z digest=sha256:fff6e64aafde03ffb16b6e428fbc4d5fd0315de8a9749409c37e1009b98e28db

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=sha256:3570e3a960d11c043d5de3fe918b188621bee9fd96894002cf968dd2c09b2ca4

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=sha256:1cded4d49894f09d0a79fd64dfc9c8a91b140b15b84102fa8e374f6a9f322bc0

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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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:15.895061Z digest=sha256:705016c7b2a541e8054f21f08db2172b77a4941c26733a3632d436b9b4e871ca

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=sha256:9f0af5b47413e978aeff72de93577d4846e07a54d47e3caadcb2b2b2f57aa5f1

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=sha256:0d753b4f55eb62011eb35e29e7b74319e5d93f468966230aa0948808b96e41c5

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=sha256:9ccfd400cfe99f4e4af03cd9ad70d42c099da42decb380b3d525b057ae5b175c

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 2026-08-18T06:34:40.430872+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=sha256:3652f28aac202c60a79a39b380c18ccb9532f6c02da8da517c547e7db5671009

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.096594Z digest=sha256:cbe8ff4ffb49668152a4a0264880eec70a9633fde0b4ca935deb52cf584fe6b9

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.114723Z digest=sha256:0fdeae19a72e9461e558d9c89c7c3448938a3d695abd0c005e7adf8ac8e2d4a0

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.123092Z digest=sha256:6c3fbc01384c522f3ef0e7c04e49cc890c541d9fbd993f2d48c41500d735b93e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.140945Z digest=sha256:47a9d0b459073f6785d2d1522a600501f5d33a714a9b4a0df3aa6aee03593a90

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.159702Z digest=sha256:f8abefe40773151b9122c4456f40e1429487d73480807756fe1ff072e99b94ff

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=sha256:2111a6f8b6618b93d5974bb6de2373eb6e8709bfaef78db057838af9ce00b52d

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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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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
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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.198567Z digest=sha256:f7610e82408f3e260b1df21edaf882cd1a419d09e4d1ee366d827ded76af292e

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=sha256:0fe36d3fa7dc629267ee55958b83e1170fbb4683131fd6357506d72f1784da44

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.221236Z digest=sha256:2bee64fb9ad5aaccc227f1f943de233ec7d49bc6ca9e55c060406174076f662b

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=sha256:2c650c1f8a6007b54f308e0303e20d085caf5348aad76e14f86da2d30234471b

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:f57b5edd7a551c678d2e9097b6740dd58d9d98618dbd43e713c67acd8531ca2b

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:bfe77c4a7c1078a61898c3284b96288a5259c2c933e0965855b6f7357d563b6e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.278863Z digest=sha256:f424ea78d808107938ac14ba576f0d72f061137164590b07c038c9ced4445d5c

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=sha256:6dece3e5b8e99a2560025eda16602caad2b8a133be61aee03cf61851dfd7b199

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.324254Z digest=sha256:8fbc19cb6cd9b79c5d7fe75ac927c6dc26efe7bc7561c163e54981963f5a8e4f

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.373478Z digest=sha256:7a805e63ec5f9ed77a964b5eaa4ea21d5fd24febfc2ecec92219a1fef890832b

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=sha256:5ff9d3f00e98437b947d31f22aefce24ff4135567557eb800df85237615e28d7

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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source=pdf_text observed=2026-08-07T11:03:17.412046Z digest=sha256:a7719f4975cad5efd3dc7327f40b11f6fea047aa40bc8a8d90e6250c40651fa4

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:17.417243Z digest=sha256:2ead0c81df131a713daabd1e8dafed1ad355e2ca81ff0cce18b1a9d8ff0da4f4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.422077Z digest=sha256:4fd846f98fcbc5b11efa8c59c272849e0c317c82c1fe6cd2a407b30e0df6360d

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:a33dd6ae0a17413d5ab6ba1a913e58dcde09725f318bd690b8e1098c612fbc78

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=sha256:0352fe835dd8d1d3f119fc4f88c6abaa29cb8fefbab02aa2c7663367a4bcca67

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.446303Z digest=sha256:8c0cc50fe932c6f7052bc0a927160a7df2bab64ffce939deac8fae7ff85a0320

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.452943Z digest=sha256:8bbc86884b28bf878c18b4d2d95fc5bcd27a651f758ac9036c160814ab39cebd

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:b47a32a52987f95f68a42aa35655ded451b6da4a53ff2d808f3974c7c441c89f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.478606Z digest=sha256:4358530fca8cb12c3eca659f2adc6eae217d52544125bff28cf46b021c04540e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.486393Z digest=sha256:d9f20df203a223a8977d5bbf3cfc19a0a34f90f02dcb7bb30249cc71cd7dff20

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.493114Z digest=sha256:af63bf08664a5ae054f09501694f7236fb9e456719acf2971dec42ef7d117cf9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.501418Z digest=sha256:f1eadb582b3f7c8f604f3652fc311329440d59313fcc2d8af772a5fcc2a27c4f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.508488Z digest=sha256:0f4781a27f56e900fa949f6cf7648a80441d63b0736509eece998b7620d5737a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.514067Z digest=sha256:aa820587c06d58ab829250522cf77f1e37c48dd2d931e23586e337e6732c3147

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.519444Z digest=sha256:0216259e1fed0bb4a262b23f0799288ad85ee7311edb2da235c437d13915380e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:03:17.525121Z digest=sha256:e8bf746235c1d593504fa455eb9864b0c8eb9b699edf9c696cd633c191dff100

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-18T18:56:48.722344Z digest=sha256:f4488b01f5dc73f55c1180c1f41d93410d24b552814ab12e5a62e56d4d04a731

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

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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=sha256:37a27a8bdfbc27ce4990494dbb12a15b706c69517065f712c21a95c495e0178f

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-13T00:58:28.483037Z digest=sha256:1851c1d3b045563a4fdaac7b6595c2b1cb980585c0f48827b259321ed5726217

Observation 27e241a0-8af7-4d23-b8bd-08bdff1db90c · inbound

Power law graph attention: exact generalization of scaled dot-product attention, empirical collapse at inference cites this paper.

Power law graph attention: exact generalization of scaled dot-product attention, empirical collapse at inference ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

Reference 48

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unresolved
no resolver link, observed 2026-08-14T04:15:48.995099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:15:48.995099Z digest=sha256:4f6275d9f6e32177183c667176f4b2064805e248c3b78caec3864cc11ca486f5

Observation db96c3ec-c7a3-424f-bb42-a5d9a0a0dfdf · inbound

When Local Variance Optimality Is Not Enough: RoPE-Aligned Q/K Rotations for Dynamic 4-Bit Quantisation cites this paper.

When Local Variance Optimality Is Not Enough: RoPE-Aligned Q/K Rotations for Dynamic 4-Bit Quantisation ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-14T12:54:26.642378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T12:54:26.642378Z digest=sha256:25805c508128c969b9e6244db876d5e1a677e31bb93e0f97763f0c64eadac12b