Paper Citation Record · LEDGER

VideoRoPE: What Makes for Good Video Rotary Position Embedding?

As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 17 inbound Pith citation observations for arXiv:2502.05173.

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

pith.paper-citation-record.v1
2502.05173 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:06:35.255089Z

measured 56 of 56 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:06:51.998314Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:37.598350Z

Reference resolution

39 of 39 outbound references displayed

verified exact1
verified fuzzy7
unresolved31
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b5837546-afe1-4b76-bd4d-509e4deaf5f0 · outbound

This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.088592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2077bea-ac2a-447b-a03e-e843b71bea30 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.093340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07a9bb7b-6e13-4cfc-b409-9f359f324945 · outbound

This paper cites The Llama 3 Herd of Models.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? The Llama 3 Herd of Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.107957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a484ea4-8fc3-41f7-9399-a6d86d273de6 · outbound

This paper cites VideoHallucer classifies hallucinations into two primary types: intrinsic and extrinsic.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? VideoHallucer classifies hallucinations into two primary types: intrinsic and extrinsic

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.887283Z

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.

Observation d5a95be9-768f-49d8-8e48-89b5465b8e14 · outbound

This paper cites TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:06:35.593964Z

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.

Observation 5b65fabf-b039-4a63-85c7-3f1263918e07 · outbound

This paper cites Accessed: 2025-01-12.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Accessed: 2025-01-12

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.914386Z

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.

Observation 9e69fc2f-6a95-4bfe-b89b-12d3a77ec5cb · outbound

This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.126322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76ce522a-51f9-4e33-8d59-0eba8a33ac6e · outbound

This paper cites VTimeLLM: Empower LLM to Grasp Video Moments.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? VTimeLLM: Empower LLM to Grasp Video Moments

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.130897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef1c0de-4222-4e57-86c7-2db6cc064039 · outbound

This paper cites OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.135448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23cc5c99-1f77-4c8e-bf47-d466a50145bb · outbound

This paper cites The Kinetics Human Action Video Dataset.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? The Kinetics Human Action Video Dataset

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.140418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b932cf2e-e01e-46e7-920c-29be7c7953f8 · outbound

This paper cites Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.144695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c19d6d-75bc-4eab-a81e-bf1ba7233419 · outbound

This paper cites Temporal Reasoning Transfer from Text to Video.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Temporal Reasoning Transfer from Text to Video

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.149060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4f5f3d-1bd8-4344-9e74-500a973541fc · outbound

This paper cites OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.153650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e1d8574-032b-4117-ab75-eb7050bd2c38 · outbound

This paper cites Valley: Video Assistant with Large Language model Enhanced abilitY.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Valley: Video Assistant with Large Language model Enhanced abilitY

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.158259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f387f90c-54ba-4c63-ba1a-e9d1f17789f5 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? YaRN: Efficient Context Window Extension of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.162915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a52dff9-a257-442d-8a57-e889f9000459 · outbound

This paper cites Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.167362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84713aff-4810-4419-91c5-4a46ad3647e9 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Learning Transferable Visual Models From Natural Language Supervision

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.172033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17f81594-282b-48cc-9b24-50ae266d3f7a · outbound

This paper cites doi: 10.1007/s11633-024-1502-8.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? doi: 10.1007/s11633-024-1502-8

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.176439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b43b4771-904a-462c-b813-dbae6baa87fc · outbound

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

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Gemma: Open Models Based on Gemini Research and Technology

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.180843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec2a373d-f810-4828-a02f-1d37a7f2e28d · outbound

This paper cites ChatVideo: A Tracklet-centric Multimodal and Versatile Video Understanding System.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? ChatVideo: A Tracklet-centric Multimodal and Versatile Video Understanding System

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.185621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3afbc6e1-ba68-4238-9002-d88ba44221df · outbound

This paper cites PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.194856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f45b970-b8b4-4627-9524-83ad999afd2a · outbound

This paper cites VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.199614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072338a1-9646-41b7-81b0-5e858610cf05 · outbound

This paper cites PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.204077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06e9e869-3a66-4c50-8bca-eb4abcc7a6d2 · outbound

This paper cites Qwen2 Technical Report.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Qwen2 Technical Report

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.208740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4118f63-dd22-44cc-943a-d3c28a5d7eef · outbound

This paper cites InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.213153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b51070d-d63d-4fc0-976a-77c714bd43a5 · outbound

This paper cites Long-CLIP: Unlocking the Long-Text Capability of CLIP.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Long-CLIP: Unlocking the Long-Text Capability of CLIP

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.217443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5d1cee3-db0c-4fd8-b453-1aa778b5ed74 · outbound

This paper cites LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.222155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78137972-cb66-4640-99b0-572721a6272b · outbound

This paper cites , y, y, y,.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? , y, y, y,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.901230Z

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.

Observation fb0685fe-619e-4eb5-9965-c775bdf2a6bd · outbound

This paper cites Extending these models to video requires handling temporal dependencies (Xu et al., 2021; Lei et al., 2021; Bertasius et al., 2021; Huang et al.,.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Extending these models to video requires handling temporal dependencies (Xu et al., 2021; Lei et al., 2021; Bertasius et al., 2021; Huang et al.,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.872041Z

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.

Observation 74a37008-fa0c-4e64-a6d0-9b890e4bda00 · outbound

This paper cites Early video LLMs, such as Wang et al.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Early video LLMs, such as Wang et al

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.858338Z

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.

Observation d6d43b69-749f-471f-88cc-e8ecd5dc073f · outbound

This paper cites However, video haystack retrieval still lags in difficulty compared with the QA or retrieval task in NLP (Hsieh et al., 2024; Yuan et al., 2024).

VideoRoPE: What Makes for Good Video Rotary Position Embedding? However, video haystack retrieval still lags in difficulty compared with the QA or retrieval task in NLP (Hsieh et al., 2024; Yuan et al., 2024)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.844073Z

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.

Observation 208dd9a1-187b-4412-85a0-d387598f8d00 · outbound

This paper cites an unresolved cited work.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-08T20:06:35.830372Z

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.

Observation d8f62f04-0191-4f40-b2c4-170ecfbe2b63 · outbound

This paper cites On the other hand, VideoRoPE employs low-frequency temporal modeling, allowing it to capture long-range dependencies and successfully identify the needle for accurate responses.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? On the other hand, VideoRoPE employs low-frequency temporal modeling, allowing it to capture long-range dependencies and successfully identify the needle for accurate responses

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:06:35.717033Z

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.

Observation 42257403-172b-49d9-ab51-fb888b0324de · outbound

This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.112479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c564a8a0-6674-415b-bf39-4b706af6b661 · outbound

This paper cites Is Space-Time Attention All You Need for Video Understanding?.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Is Space-Time Attention All You Need for Video Understanding?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.083369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc9bac64-023a-4caa-b918-1bec63136a6a · outbound

This paper cites InternVideo: General Video Foundation Models via Generative and Discriminative Learning.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.190284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c48653a7-17e7-4649-b1f8-6273adf43fdc · outbound

This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.097848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5beaa9dd-d781-4b65-9da0-1da05671958c · outbound

This paper cites Pixtral 12B.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? Pixtral 12B

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.077993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcb314c8-8f4f-48c6-94cf-730a25f6fc0d · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

VideoRoPE: What Makes for Good Video Rotary Position Embedding? LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:35.102689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0c8f2209-5d3c-42fd-ab0c-1e4749873c54 · inbound

ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images cites this paper.

ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T17:26:28.859252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d0f781a-f4a6-4cfc-91ce-56a209cd6d6a · inbound

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation cites this paper.

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:24:04.687193Z

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.

Observation a78a7883-6d7d-4472-902f-582dae61d412 · inbound

Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models cites this paper.

Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:21:39.810267Z

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.

Observation 72d0da19-90bd-49a7-bad9-1dce2fcd7bc2 · inbound

EVA02-AT: Egocentric Video-Language Understanding with Spatial-Temporal Rotary Positional Embeddings and Symmetric Optimization cites this paper.

EVA02-AT: Egocentric Video-Language Understanding with Spatial-Temporal Rotary Positional Embeddings and Symmetric Optimization VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:26:03.315947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a909771-f00d-4697-acda-ccf2c2a7a875 · inbound

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification cites this paper.

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T23:13:11.715462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 333a114b-7802-40da-aee7-bd656b079e76 · inbound

Task-Aware KV Compression For Cost-Effective Long Video Understanding cites this paper.

Task-Aware KV Compression For Cost-Effective Long Video Understanding VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T22:36:38.968114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f519b7f8-72c3-4347-acda-48ca2a008599 · inbound

Infinite Video Understanding cites this paper.

Infinite Video Understanding VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T18:10:14.257348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 403e88a9-0bf6-44aa-8100-3224b1e886ed · inbound

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture cites this paper.

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T11:40:23.835237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bccfc75-5faa-4730-9dad-5d0766c30932 · inbound

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer cites this paper.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 115

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:38.274053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 267f2f9f-3cd4-4d5e-b8d4-ef00846bdc9d · inbound

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models cites this paper.

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:06:07.573803Z

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.

Observation 12933e0b-01a1-4e67-bb01-f81fd46e42b4 · inbound

Diffusing in the Right Space: A Systematic Study of Latent Diffusability cites this paper.

Diffusing in the Right Space: A Systematic Study of Latent Diffusability VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:36:27.600377Z

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.

Observation 2a713525-41ae-4314-9492-796073ef8e62 · inbound

LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution cites this paper.

LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.629230Z

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.

Observation afdacdee-a5a5-485e-8d91-d3428a46e6e3 · inbound

HPP: Hierarchical Programmatic Probing for Long Video Understanding by Decoupling Perception and Reasoning cites this paper.

HPP: Hierarchical Programmatic Probing for Long Video Understanding by Decoupling Perception and Reasoning VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 130

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T06:39:37.599608Z

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.

Observation 5f6635f3-64b7-44be-b639-c611f485d09c · inbound

ShotPlan: Cinematic Video Generation with Learnable Planning Token cites this paper.

ShotPlan: Cinematic Video Generation with Learnable Planning Token VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T17:22:32.782701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac47fea1-aa70-403c-8d35-88a576e228ee · inbound

ChronoStitch: Training-Free Composition of Visual KV Memories for Long-Horizon Temporal Reasoning cites this paper.

ChronoStitch: Training-Free Composition of Visual KV Memories for Long-Horizon Temporal Reasoning VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T12:28:00.977584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 387af61f-359b-4b3a-8569-d5f16007ec61 · inbound

RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring cites this paper.

RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T09:52:44.291024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf6b92ab-aa87-4a59-8ff8-96e0a87c7b1b · inbound

Addressable Memory for Video World Models cites this paper.

Addressable Memory for Video World Models VideoRoPE: What Makes for Good Video Rotary Position Embedding?

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-10T05:06:51.998314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.