Paper Citation Record · LEDGER

VideoOrion: Tokenizing Object Dynamics in Videos

As of 19 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 3 inbound Pith citation observations for arXiv:2411.16156.

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

pith.paper-citation-record.v1
2411.16156 v2

Coverage vector

measured 80 of 80 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:34:39.675979Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:43:42.424641Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:33:51.653731Z

Reference resolution

80 of 80 outbound references displayed

verified exact1
verified fuzzy43
unresolved35
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 082cb338-6733-437d-8440-5807cad345cf · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

VideoOrion: Tokenizing Object Dynamics in Videos Flamingo: a visual language model for few-shot learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.307583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af876d63-93b8-4127-b704-b78283d9d226 · outbound

This paper cites Spice: Semantic propositional image cap- tion evaluation.

VideoOrion: Tokenizing Object Dynamics in Videos Spice: Semantic propositional image cap- tion evaluation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.878283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation deaab55d-cf4c-4f53-a562-18c9852652f8 · outbound

This paper cites MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens.

VideoOrion: Tokenizing Object Dynamics in Videos MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.318256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf5ccdd3-4d13-4689-9b36-8a0474465e1b · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

VideoOrion: Tokenizing Object Dynamics in Videos Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.323403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc23c52c-b1bb-4bbd-a989-988ccd54b296 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments.

VideoOrion: Tokenizing Object Dynamics in Videos Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.863841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 97bff7b1-14ee-44b5-91b8-a57ddaa2f10e · outbound

This paper cites O’Reilly Media, Inc.

VideoOrion: Tokenizing Object Dynamics in Videos O’Reilly Media, Inc

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.848409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a1d00ac4-016f-4473-9f03-864bc1a8fed2 · outbound

This paper cites TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models.

VideoOrion: Tokenizing Object Dynamics in Videos TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.338126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cebda45f-0aa7-48a2-8008-19870e9c55de · outbound

This paper cites End-to- end object detection with transformers.

VideoOrion: Tokenizing Object Dynamics in Videos End-to- end object detection with transformers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.342772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 932aee05-fa87-458e-9788-4c094850c421 · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

VideoOrion: Tokenizing Object Dynamics in Videos MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.348006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2ae6eec-bd68-44f2-ba7a-00b1f27df4a0 · outbound

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

VideoOrion: Tokenizing Object Dynamics in Videos ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.353218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0092740a-55b1-443c-adae-32a5323b2559 · outbound

This paper cites Weakly-Supervised Spatio-Temporally Grounding Natural Sentence in Video.

VideoOrion: Tokenizing Object Dynamics in Videos Weakly-Supervised Spatio-Temporally Grounding Natural Sentence in Video

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-12T13:34:40.052973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e861eb7f-5a85-464b-bee9-91f7f341c223 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

VideoOrion: Tokenizing Object Dynamics in Videos Masked-attention mask transformer for universal image segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.821627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9669a69-5820-4882-bc4f-c4e15f5f35fd · outbound

This paper cites an unresolved cited work.

VideoOrion: Tokenizing Object Dynamics in Videos Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:34:40.806599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b9c46bf-5595-42df-9718-aad066aba0a6 · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

VideoOrion: Tokenizing Object Dynamics in Videos VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.372277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9c51a8f-5985-4fb2-9a44-85d4ddf0a131 · outbound

This paper cites Study on density peaks clustering based on k-nearest neighbors and principal component analysis.

VideoOrion: Tokenizing Object Dynamics in Videos Study on density peaks clustering based on k-nearest neighbors and principal component analysis

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.791637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e1ec2af-f5dd-4f42-a043-69003f616162 · outbound

This paper cites The Llama 3 Herd of Models.

VideoOrion: Tokenizing Object Dynamics in Videos The Llama 3 Herd of Models

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07554d6f-ad94-4742-b382-66b35f7d7893 · outbound

This paper cites Lasot: A high-quality benchmark for large-scale single ob- ject tracking.

VideoOrion: Tokenizing Object Dynamics in Videos Lasot: A high-quality benchmark for large-scale single ob- ject tracking

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.775737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba229878-cdc1-4eb7-b44e-6e039950c3e3 · outbound

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

VideoOrion: Tokenizing Object Dynamics in Videos Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.391033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20f0309b-697f-4c1b-9de5-d049e595a65a · outbound

This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.

VideoOrion: Tokenizing Object Dynamics in Videos Ego4d: Around the world in 3,000 hours of egocentric video

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.396197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af730cfc-bc5f-4ac0-a6d2-ca3f8a0ada80 · outbound

This paper cites Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives.

VideoOrion: Tokenizing Object Dynamics in Videos Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.750917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2fee7f5-8897-4d27-9be6-221d9f1a8e6a · outbound

This paper cites Mask r-cnn.

VideoOrion: Tokenizing Object Dynamics in Videos Mask r-cnn

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.735797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a837cb10-ca46-4f9d-9b4f-003abde76505 · outbound

This paper cites Long short-term memory.

VideoOrion: Tokenizing Object Dynamics in Videos Long short-term memory

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.721460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4048b125-cb13-4ab1-8779-250abed61461 · outbound

This paper cites Open-set image tagging with multi-grained text su- pervision.

VideoOrion: Tokenizing Object Dynamics in Videos Open-set image tagging with multi-grained text su- pervision

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.706550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 27dda32e-8e56-41b3-9a0e-9e72dc2d10e2 · outbound

This paper cites Mistral 7B.

VideoOrion: Tokenizing Object Dynamics in Videos Mistral 7B

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 943b5a7f-97fb-4bef-afc4-af9386306b3b · outbound

This paper cites Chat-univi: Unified visual representation em- powers large language models with image and video under- standing.

VideoOrion: Tokenizing Object Dynamics in Videos Chat-univi: Unified visual representation em- powers large language models with image and video under- standing

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.691466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a52bde1e-85df-45ec-a38c-8608fa117d4c · outbound

This paper cites Video-lavit: Unified video-language pre-training with decoupled visual-motional tokenization.

VideoOrion: Tokenizing Object Dynamics in Videos Video-lavit: Unified video-language pre-training with decoupled visual-motional tokenization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.675832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9b26ce3e-57e1-479e-b162-949fb9a0ecd2 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross B.

VideoOrion: Tokenizing Object Dynamics in Videos Berg, Wan-Yen Lo, Piotr Dollár, and Ross B

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.658394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3f710ebf-d498-47c5-91e2-489872a8fd1e · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

VideoOrion: Tokenizing Object Dynamics in Videos LLaVA-OneVision: Easy Visual Task Transfer

Reference 28

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Source-reported events for the cited work

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Observation 07656d73-a75f-4797-a617-fe01cf21ae03 · outbound

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VideoOrion: Tokenizing Object Dynamics in Videos Unresolved cited work

Reference 29

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Source-reported events for the cited work

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Observation e8afc645-a8f4-490b-94fe-c1f5f3c39382 · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

VideoOrion: Tokenizing Object Dynamics in Videos VideoChat: Chat-Centric Video Understanding

Reference 30

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Source-reported events for the cited work

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Observation e33e0842-ee4d-4e7c-b7f6-e2896ce0751e · outbound

This paper cites Unmasked teacher: Towards training-efficient video foundation models.

VideoOrion: Tokenizing Object Dynamics in Videos Unmasked teacher: Towards training-efficient video foundation models

Reference 31

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Source-reported events for the cited work

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Observation e834733b-c25a-4f95-a7ef-0e177f43659c · outbound

This paper cites Mvbench: A comprehensive multi-modal video understand- ing benchmark.

VideoOrion: Tokenizing Object Dynamics in Videos Mvbench: A comprehensive multi-modal video understand- ing benchmark

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.614415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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This paper cites LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models.

VideoOrion: Tokenizing Object Dynamics in Videos LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models

Reference 33

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Source-reported events for the cited work

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Observation 43f120a1-72eb-4099-9685-eef9b93fb36c · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

VideoOrion: Tokenizing Object Dynamics in Videos Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 34

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Source-reported events for the cited work

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This paper cites Rouge: A package for automatic evaluation of summaries.

VideoOrion: Tokenizing Object Dynamics in Videos Rouge: A package for automatic evaluation of summaries

Reference 35

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Observation 6dd8a0b1-f04e-40ac-9649-6e70ebf69249 · outbound

This paper cites Visual instruction tuning.

VideoOrion: Tokenizing Object Dynamics in Videos Visual instruction tuning

Reference 36

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Observation 555b8592-3df8-477c-bbd9-9ef5a4f87786 · outbound

This paper cites Visual instruction tuning.

VideoOrion: Tokenizing Object Dynamics in Videos Visual instruction tuning

Reference 37

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Observation 5f942323-284f-4900-85b3-28d0515c65db · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

VideoOrion: Tokenizing Object Dynamics in Videos Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 38

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

VideoOrion: Tokenizing Object Dynamics in Videos Valley: Video Assistant with Large Language model Enhanced abilitY

Reference 39

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Source-reported events for the cited work

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This paper cites Video-chatgpt: Towards detailed video un- derstanding via large vision and language models.

VideoOrion: Tokenizing Object Dynamics in Videos Video-chatgpt: Towards detailed video un- derstanding via large vision and language models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.558291Z

Source-reported events for the cited work

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Observation f986b07a-4e33-4c13-8e73-80c41666a413 · outbound

This paper cites Trackflow: Multi-object tracking with normalizing flows.

VideoOrion: Tokenizing Object Dynamics in Videos Trackflow: Multi-object tracking with normalizing flows

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.542588Z

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Observation 20f76415-9d50-4e21-b82c-c1e899309713 · outbound

This paper cites Egoschema: A diagnostic benchmark for very long- form video language understanding.

VideoOrion: Tokenizing Object Dynamics in Videos Egoschema: A diagnostic benchmark for very long- form video language understanding

Reference 42

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Observation 7f15f85d-ee84-45c8-a936-81a6ae8bf117 · outbound

This paper cites Trackformer: Multi-object track- ing with transformers.

VideoOrion: Tokenizing Object Dynamics in Videos Trackformer: Multi-object track- ing with transformers

Reference 43

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This paper cites OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.

VideoOrion: Tokenizing Object Dynamics in Videos OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 44

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VideoOrion: Tokenizing Object Dynamics in Videos GPT-4 Technical Report

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This paper cites DINOv2: Learning Robust Visual Features without Supervision.

VideoOrion: Tokenizing Object Dynamics in Videos DINOv2: Learning Robust Visual Features without Supervision

Reference 46

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This paper cites Bleu: a method for automatic evaluation of machine translation.

VideoOrion: Tokenizing Object Dynamics in Videos Bleu: a method for automatic evaluation of machine translation

Reference 47

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Source-reported events for the cited work

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Observation 22a51f1b-ccec-4d26-b9ba-17290cd0476e · outbound

This paper cites Per- ception test: A diagnostic benchmark for multimodal video models.

VideoOrion: Tokenizing Object Dynamics in Videos Per- ception test: A diagnostic benchmark for multimodal video models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.487829Z

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Observation c6329891-fbc4-4738-94cb-4d3a726e4484 · outbound

This paper cites Learning video object segmentation from static images.

VideoOrion: Tokenizing Object Dynamics in Videos Learning video object segmentation from static images

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.473007Z

Source-reported events for the cited work

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Observation 8d531abf-a8fa-4427-83f0-d229a48a7a6f · outbound

This paper cites Towards generalizable multi-object tracking.

VideoOrion: Tokenizing Object Dynamics in Videos Towards generalizable multi-object tracking

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.458607Z

Source-reported events for the cited work

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Observation ef256bd6-26c1-47a5-b89f-56f0594d45ed · outbound

This paper cites Artemis: Towards Referential Understanding in Complex Videos.

VideoOrion: Tokenizing Object Dynamics in Videos Artemis: Towards Referential Understanding in Complex Videos

Reference 51

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Source-reported events for the cited work

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

VideoOrion: Tokenizing Object Dynamics in Videos Learning transferable visual models from natural language supervision

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.444157Z

Source-reported events for the cited work

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Observation b691f4ac-b038-4075-85d5-023e827df575 · outbound

This paper cites Girshick, Kaiming He, and Piotr Dollár.

VideoOrion: Tokenizing Object Dynamics in Videos Girshick, Kaiming He, and Piotr Dollár

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.429322Z

Source-reported events for the cited work

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Observation 41085d68-300e-4ec1-8543-0d927b5a5a7b · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

VideoOrion: Tokenizing Object Dynamics in Videos SAM 2: Segment Anything in Images and Videos

Reference 54

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Source-reported events for the cited work

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Observation 75c5a13f-1a39-468d-8cd4-8e9ba56ed472 · outbound

This paper cites Timechat: A time-sensitive multimodal large lan- guage model for long video understanding.

VideoOrion: Tokenizing Object Dynamics in Videos Timechat: A time-sensitive multimodal large lan- guage model for long video understanding

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.414521Z

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Observation ddc4fce0-dfad-44e3-8ba3-5032e811122a · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

VideoOrion: Tokenizing Object Dynamics in Videos Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.399619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c6ac71a1-b325-4977-9043-49cd8aaacf96 · outbound

This paper cites Audio-Visual LLM for Video Understanding.

VideoOrion: Tokenizing Object Dynamics in Videos Audio-Visual LLM for Video Understanding

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.568890Z

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Observation 9928d5cb-9c40-414b-a00d-4b1ceb7893ec · outbound

This paper cites Human-centric spatio-temporal video grounding with visual transformers.

VideoOrion: Tokenizing Object Dynamics in Videos Human-centric spatio-temporal video grounding with visual transformers

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.383909Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ef7c6d51-f861-41bb-8bfa-d15ffe57826f · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

VideoOrion: Tokenizing Object Dynamics in Videos Gemini: A Family of Highly Capable Multimodal Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.578928Z

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Observation 35e36e0d-49fa-4b6a-af1e-137242892064 · outbound

This paper cites Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training.

VideoOrion: Tokenizing Object Dynamics in Videos Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.369223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7411bd11-f04d-447e-80ee-fc3989d1c959 · outbound

This paper cites Attention is all you need.

VideoOrion: Tokenizing Object Dynamics in Videos Attention is all you need

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.354099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3d6b349-5e81-4d83-964c-bae5123daf8c · outbound

This paper cites Cider: Consensus-based image description evalua- tion.

VideoOrion: Tokenizing Object Dynamics in Videos Cider: Consensus-based image description evalua- tion

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.337957Z

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Observation f3cb8cb6-8b87-407f-a60d-5feea461e2a3 · outbound

This paper cites Elysium: Exploring object-level perception in videos via mllm.

VideoOrion: Tokenizing Object Dynamics in Videos Elysium: Exploring object-level perception in videos via mllm

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.323665Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fb45a14-08ee-4ea3-8ee4-d0de5f67d7fd · outbound

This paper cites Fast online object tracking and segmentation: A unifying approach.

VideoOrion: Tokenizing Object Dynamics in Videos Fast online object tracking and segmentation: A unifying approach

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.308679Z

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Observation 8e6574c4-d365-452b-b334-4bf7b58b55fe · outbound

This paper cites Internvid: A large-scale video-text dataset for multimodal understanding and generation.

VideoOrion: Tokenizing Object Dynamics in Videos Internvid: A large-scale video-text dataset for multimodal understanding and generation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.293812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2e85e2f-10f1-4f0e-b5ab-5d91d0d6dd13 · outbound

This paper cites Slot-VLM: SlowFast Slots for Video-Language Modeling.

VideoOrion: Tokenizing Object Dynamics in Videos Slot-VLM: SlowFast Slots for Video-Language Modeling

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.611300Z

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Observation 53b2039b-2828-4a06-a1d8-2a012de8fc73 · outbound

This paper cites Qwen2 Technical Report.

VideoOrion: Tokenizing Object Dynamics in Videos Qwen2 Technical Report

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.616540Z

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Observation a5140dd1-eccf-4722-9257-f3a321c32961 · outbound

This paper cites Associating ob- jects with transformers for video object segmentation.

VideoOrion: Tokenizing Object Dynamics in Videos Associating ob- jects with transformers for video object segmentation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.278454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db39b2ad-338f-496f-a2c0-7588327cd4a3 · outbound

This paper cites Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection.

VideoOrion: Tokenizing Object Dynamics in Videos Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.626487Z

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Observation 5a20671a-cbc3-4966-8533-f1dbd5445e5b · outbound

This paper cites Ferret: Refer and Ground Anything Anywhere at Any Granularity.

VideoOrion: Tokenizing Object Dynamics in Videos Ferret: Refer and Ground Anything Anywhere at Any Granularity

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.630943Z

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Observation fffe4e55-fa70-4c75-a895-f187e12bac3c · outbound

This paper cites Merlin: Empowering multimodal llms with foresight minds.

VideoOrion: Tokenizing Object Dynamics in Videos Merlin: Empowering multimodal llms with foresight minds

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.253003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 809c6341-9e23-46dd-8906-80cca33510bc · outbound

This paper cites Activitynet-qa: A dataset for understanding complex web videos via question answering.

VideoOrion: Tokenizing Object Dynamics in Videos Activitynet-qa: A dataset for understanding complex web videos via question answering

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.238026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7d14f471-a06e-4225-b9e9-e82064e228f9 · outbound

This paper cites Sigmoid loss for language image pre-training.

VideoOrion: Tokenizing Object Dynamics in Videos Sigmoid loss for language image pre-training

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.644411Z

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Observation daa19f54-10a2-4e35-94fb-d26a5579b75c · outbound

This paper cites Ni, and Heung-Yeung Shum.

VideoOrion: Tokenizing Object Dynamics in Videos Ni, and Heung-Yeung Shum

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.211398Z

Source-reported events for the cited work

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Observation 62c6b054-d9f2-42b2-81ef-e9de295d7600 · outbound

This paper cites Video-llama: An instruction-tuned audio-visual language model for video un- derstanding.

VideoOrion: Tokenizing Object Dynamics in Videos Video-llama: An instruction-tuned audio-visual language model for video un- derstanding

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.195553Z

Source-reported events for the cited work

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Observation bdd9b020-43cb-46c0-b9b0-895f15b28c95 · outbound

This paper cites Long Context Transfer from Language to Vision.

VideoOrion: Tokenizing Object Dynamics in Videos Long Context Transfer from Language to Vision

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.658034Z

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Observation e3186eee-38ad-4f2a-963b-5e476b1e2ee5 · outbound

This paper cites Bytetrack: Multi-object tracking by associating every detection box.

VideoOrion: Tokenizing Object Dynamics in Videos Bytetrack: Multi-object tracking by associating every detection box

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.178837Z

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Observation d127ec19-20b0-4bb5-b547-4e297e93cb3f · outbound

This paper cites Llava- next: A strong zero-shot video understanding model, 2024.

VideoOrion: Tokenizing Object Dynamics in Videos Llava- next: A strong zero-shot video understanding model, 2024

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.163011Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0168b99f-74c3-484d-b4bc-03fefaf1fb3e · outbound

This paper cites Minigpt-4: Enhancing vision-language understanding with advanced large language models.

VideoOrion: Tokenizing Object Dynamics in Videos Minigpt-4: Enhancing vision-language understanding with advanced large language models

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.147418Z

Source-reported events for the cited work

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Observation c030980a-8153-4a00-9e49-f400e8b8c805 · outbound

This paper cites Tracking Anything in High Quality.

VideoOrion: Tokenizing Object Dynamics in Videos Tracking Anything in High Quality

Reference 80

Resolution: malformed identifier; no resolver link, observed 2026-08-12T13:34:39.675979Z

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Pith citing papers

Observation 33f7feff-207a-4e92-9c5b-053e6c498d97 · inbound

Enhancing Surgical Documentation through Multimodal Visual-Temporal Transformers and Generative AI cites this paper.

Enhancing Surgical Documentation through Multimodal Visual-Temporal Transformers and Generative AI VideoOrion: Tokenizing Object Dynamics in Videos

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T05:43:42.424641Z

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Observation a2c3ae77-95fe-4fe4-a46a-9825521193aa · inbound

Unified Multimodal Understanding via Byte-Pair Visual Encoding cites this paper.

Unified Multimodal Understanding via Byte-Pair Visual Encoding VideoOrion: Tokenizing Object Dynamics in Videos

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T21:41:51.372359Z

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Observation dc1b8b98-c779-4bba-ba14-eacaaf7e8583 · inbound

Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos cites this paper.

Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos VideoOrion: Tokenizing Object Dynamics in Videos

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:33:51.694013Z

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