Paper Citation Record · LEDGER

Dense360: Dense Understanding from Omnidirectional Panoramas

As of 8 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 6 inbound Pith citation observations for arXiv:2506.14471.

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

pith.paper-citation-record.v1
2506.14471 v1

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:23:56.322623Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:59:02.378826Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:48:32.614745Z

Reference resolution

79 of 79 outbound references displayed

verified exact4
verified fuzzy37
unresolved38
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be959be0-fd34-433c-879b-a19b0dea03a1 · outbound

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

Dense360: Dense Understanding from Omnidirectional Panoramas Flamingo: a visual language model for few-shot learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:44.783957Z

Source-reported events for the cited work

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Observation 32651995-8b8b-4b38-bb7f-fb3a06f05882 · outbound

This paper cites Qwen2.5-VL Technical Report.

Dense360: Dense Understanding from Omnidirectional Panoramas Qwen2.5-VL Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:44.894729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d782884f-cb52-4fbb-bcf0-99f2239acf1a · outbound

This paper cites Egok360: A 360 egocentric kinetic human activity video dataset.

Dense360: Dense Understanding from Omnidirectional Panoramas Egok360: A 360 egocentric kinetic human activity video dataset

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.236515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b58307fd-d846-45d3-869d-45d9bdfe7d55 · outbound

This paper cites Language models are few-shot learners.

Dense360: Dense Understanding from Omnidirectional Panoramas Language models are few-shot learners

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.217242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2efea0fe-10d2-4afa-a7c8-8d93ffec022c · outbound

This paper cites Vip-llava: Making large multimodal models understand arbitrary visual prompts.

Dense360: Dense Understanding from Omnidirectional Panoramas Vip-llava: Making large multimodal models understand arbitrary visual prompts

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.195601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e06b2259-2878-4394-bbee-b8d8f3106961 · outbound

This paper cites Opening the vocabulary of egocentric actions.

Dense360: Dense Understanding from Omnidirectional Panoramas Opening the vocabulary of egocentric actions

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.173880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ef5e3b6e-7fe4-40e6-98df-9a0ce3677068 · outbound

This paper cites 360+ x: A panoptic multi-modal scene understanding dataset.

Dense360: Dense Understanding from Omnidirectional Panoramas 360+ x: A panoptic multi-modal scene understanding dataset

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.151865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 26f582a5-c38a-45e7-aa96-6de5a82ce19f · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

Dense360: Dense Understanding from Omnidirectional Panoramas Sharegpt4v: Improving large multi-modal models with better captions

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.131630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5515e812-0aa4-467d-9042-d40818a0e3c8 · outbound

This paper cites A single transformer for scalable vision-language modeling.

Dense360: Dense Understanding from Omnidirectional Panoramas A single transformer for scalable vision-language modeling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.112148Z

Source-reported events for the cited work

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Observation 024bfd26-8b25-4130-b75b-49c1909b4e08 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Dense360: Dense Understanding from Omnidirectional Panoramas Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:46.230089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d60de1d-15f5-4b49-8a54-0f40757cf88a · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Dense360: Dense Understanding from Omnidirectional Panoramas Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:46.465672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72f191dc-7804-499f-9b05-e489c452f06a · outbound

This paper cites Embodied artificial intelligence.

Dense360: Dense Understanding from Omnidirectional Panoramas Embodied artificial intelligence

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.083055Z

Source-reported events for the cited work

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Observation b7511b78-29ba-4bc9-ae2a-aebebb6fba4e · outbound

This paper cites Xtuner: A toolkit for efficiently fine-tuning llm.https://github.com/InternLM/ xtuner, 2023.

Dense360: Dense Understanding from Omnidirectional Panoramas Xtuner: A toolkit for efficiently fine-tuning llm.https://github.com/InternLM/ xtuner, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.064321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 904a8184-0bd6-453c-aa97-d7264b97eaa6 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Dense360: Dense Understanding from Omnidirectional Panoramas InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:47.061342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5b82210-91d2-4cd0-bd0d-8d67505002d6 · outbound

This paper cites Bert: Pre-training of deep bidirec- tional transformers for language understanding.

Dense360: Dense Understanding from Omnidirectional Panoramas Bert: Pre-training of deep bidirec- tional transformers for language understanding

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.043410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6a10af03-a77f-46dc-9977-4ebbbfb433b1 · outbound

This paper cites Unveiling Encoder-Free Vision-Language Models.

Dense360: Dense Understanding from Omnidirectional Panoramas Unveiling Encoder-Free Vision-Language Models

Reference 16

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Source-reported events for the cited work

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Observation debf2a9a-6d76-491b-8c8b-dd7dab277001 · outbound

This paper cites EVEv2: Improved Baselines for Encoder-Free Vision-Language Models.

Dense360: Dense Understanding from Omnidirectional Panoramas EVEv2: Improved Baselines for Encoder-Free Vision-Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:47.528488Z

Source-reported events for the cited work

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Observation f2f86070-df66-42f5-a9d6-11c809cb46a6 · outbound

This paper cites PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild.

Dense360: Dense Understanding from Omnidirectional Panoramas PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:58.066400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cfb07893-49ad-4fd7-8635-d760cd3510ff · outbound

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

Dense360: Dense Understanding from Omnidirectional Panoramas An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:47.847964Z

Source-reported events for the cited work

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Observation 72ef7a60-4096-4597-8628-6641a99fa105 · outbound

This paper cites Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding.

Dense360: Dense Understanding from Omnidirectional Panoramas Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:47.969877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 391054ec-1810-4d02-8d9e-4bf38407ecfb · outbound

This paper cites On Path to Multimodal Generalist: General-Level and General-Bench.

Dense360: Dense Understanding from Omnidirectional Panoramas On Path to Multimodal Generalist: General-Level and General-Bench

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:48.104575Z

Source-reported events for the cited work

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Observation 5760e726-4493-4b38-9dc5-52cecefdc9a5 · outbound

This paper cites Scene-llm: Extending language model for 3d visual reasoning.

Dense360: Dense Understanding from Omnidirectional Panoramas Scene-llm: Extending language model for 3d visual reasoning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.024353Z

Source-reported events for the cited work

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Observation 25103cae-a729-4d1b-8808-c80a0cd947d2 · outbound

This paper cites Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs.

Dense360: Dense Understanding from Omnidirectional Panoramas Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:48.496547Z

Source-reported events for the cited work

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Observation 63b544d1-ed44-45bb-9e3c-9496c32c5084 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Dense360: Dense Understanding from Omnidirectional Panoramas LoRA: Low-Rank Adaptation of Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:48.642934Z

Source-reported events for the cited work

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Observation 4b671506-9be0-41a9-af65-515c7647b2d9 · outbound

This paper cites Open-Set Image Tagging with Multi-Grained Text Supervision.

Dense360: Dense Understanding from Omnidirectional Panoramas Open-Set Image Tagging with Multi-Grained Text Supervision

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:48.826213Z

Source-reported events for the cited work

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Observation 8018aa1f-d80d-4451-9f7c-4181c1fa703e · outbound

This paper cites An Egocentric Vision-Language Model based Portable Real-time Smart Assistant.

Dense360: Dense Understanding from Omnidirectional Panoramas An Egocentric Vision-Language Model based Portable Real-time Smart Assistant

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:48.947715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f144924f-3394-42d0-9e29-5b38d72109a4 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Dense360: Dense Understanding from Omnidirectional Panoramas Scaling up visual and vision-language representation learning with noisy text supervision

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:13.002916Z

Source-reported events for the cited work

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Observation 4fd599c9-9096-4096-8c84-8e7d39c38f15 · outbound

This paper cites Probres: Probabilistic jump diffusion for open-world egocentric activity recognition.arXiv preprint arXiv:2504.03948, 2025.

Dense360: Dense Understanding from Omnidirectional Panoramas Probres: Probabilistic jump diffusion for open-world egocentric activity recognition.arXiv preprint arXiv:2504.03948, 2025

Reference 28

Resolution: verified exact; raw_fallback, observed 2026-08-07T00:23:57.625840Z

Source-reported events for the cited work

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Observation e9f67cbd-25d5-418c-93c4-ddfa1492fc0c · outbound

This paper cites Lisa: Reasoning segmentation via large language model.

Dense360: Dense Understanding from Omnidirectional Panoramas Lisa: Reasoning segmentation via large language model

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.982741Z

Source-reported events for the cited work

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Observation 8800bf74-3110-4e41-923c-fc63c89873af · outbound

This paper cites Jrdb-panotrack: An open-world panoptic segmentation and tracking robotic dataset in crowded human environments.

Dense360: Dense Understanding from Omnidirectional Panoramas Jrdb-panotrack: An open-world panoptic segmentation and tracking robotic dataset in crowded human environments

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.964929Z

Source-reported events for the cited work

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Observation d3871d7f-5c24-4e64-bccb-7f274db91690 · outbound

This paper cites Perspective-Aware Reasoning in Vision-Language Models via Mental Imagery Simulation.

Dense360: Dense Understanding from Omnidirectional Panoramas Perspective-Aware Reasoning in Vision-Language Models via Mental Imagery Simulation

Reference 31

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Source-reported events for the cited work

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Observation d38ba6ba-aff1-4ac1-8f00-f9a7d4ddbd2c · outbound

This paper cites 360 vision, from panoramas to vr.

Dense360: Dense Understanding from Omnidirectional Panoramas 360 vision, from panoramas to vr

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.940982Z

Source-reported events for the cited work

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Observation 0a17f5af-bee7-4047-b2c9-286bc6d6a855 · outbound

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

Dense360: Dense Understanding from Omnidirectional Panoramas LLaVA-OneVision: Easy Visual Task Transfer

Reference 33

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Source-reported events for the cited work

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Observation 2c2a2053-a2a0-4883-9fcc-c0ee835181d8 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Dense360: Dense Understanding from Omnidirectional Panoramas Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.910076Z

Source-reported events for the cited work

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Observation 2cf46afd-72a6-45c8-a3f0-4bde58d04b49 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Dense360: Dense Understanding from Omnidirectional Panoramas Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.893443Z

Source-reported events for the cited work

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Observation 53a3e681-f990-4774-aa35-e5e36595ec95 · outbound

This paper cites Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.

Dense360: Dense Understanding from Omnidirectional Panoramas Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.877240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fcda15fc-7971-4ea6-a4e8-bbf00868cbbc · outbound

This paper cites Describe Anything: Detailed Localized Image and Video Captioning.

Dense360: Dense Understanding from Omnidirectional Panoramas Describe Anything: Detailed Localized Image and Video Captioning

Reference 37

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Observation 33bf2b50-7b2d-4cab-ba1f-85b59c7f2649 · outbound

This paper cites Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d.

Dense360: Dense Understanding from Omnidirectional Panoramas Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.860092Z

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Observation 98d2bef8-dc94-43b7-8aa2-912ffb4d41d9 · outbound

This paper cites URECA: Unique Region Caption Anything.

Dense360: Dense Understanding from Omnidirectional Panoramas URECA: Unique Region Caption Anything

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:57.190251Z

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Observation d7958a0b-fe53-49c7-8d92-40687e2fed69 · outbound

This paper cites Egocentric video-language pretraining.

Dense360: Dense Understanding from Omnidirectional Panoramas Egocentric video-language pretraining

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.835680Z

Source-reported events for the cited work

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Observation dd89bfea-ac48-46be-98d0-e745b4cca1ff · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

Dense360: Dense Understanding from Omnidirectional Panoramas Improved Baselines with Visual Instruction Tuning

Reference 41

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Observation 0cfcb187-889b-4b07-90a5-65fa15f988b6 · outbound

This paper cites Improved baselines with visual instruction tuning.

Dense360: Dense Understanding from Omnidirectional Panoramas Improved baselines with visual instruction tuning

Reference 42

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Source-reported events for the cited work

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Observation c9583332-e5d8-46d9-89d1-116dbbac691b · outbound

This paper cites Visual Instruction Tuning.

Dense360: Dense Understanding from Omnidirectional Panoramas Visual Instruction Tuning

Reference 43

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Observation 8a472254-7516-4baa-82ce-39d4cff1595a · outbound

This paper cites Visual instruction tuning.

Dense360: Dense Understanding from Omnidirectional Panoramas Visual instruction tuning

Reference 44

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Source-reported events for the cited work

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Observation e2cc3e1e-8fd0-4759-9e38-edfef6bbb4ff · outbound

This paper cites Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement.

Dense360: Dense Understanding from Omnidirectional Panoramas Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Reference 45

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Source-reported events for the cited work

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Observation 24d36956-d58a-44a5-909a-76f98353b364 · outbound

This paper cites Vmamba: Visual state space model.

Dense360: Dense Understanding from Omnidirectional Panoramas Vmamba: Visual state space model

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.778073Z

Source-reported events for the cited work

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Observation ba97da9a-fc7a-4f93-9576-2677d660d8bd · outbound

This paper cites Mono-internvl: Pushing the boundaries of monolithic multimodal large language models with endogenous visual pre-training.

Dense360: Dense Understanding from Omnidirectional Panoramas Mono-internvl: Pushing the boundaries of monolithic multimodal large language models with endogenous visual pre-training

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.758898Z

Source-reported events for the cited work

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Observation 4e6d7fd3-13bc-4b76-952b-ad5ea10882ba · outbound

This paper cites Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models.

Dense360: Dense Understanding from Omnidirectional Panoramas Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:52.717672Z

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Observation 15beec1b-391e-4abc-9db7-631f8f3b942e · outbound

This paper cites WMNav: Integrating Vision-Language Models into World Models for Object Goal Navigation.

Dense360: Dense Understanding from Omnidirectional Panoramas WMNav: Integrating Vision-Language Models into World Models for Object Goal Navigation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:52.841824Z

Source-reported events for the cited work

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Observation 30f9e984-28d7-4785-b32b-c9692a9bcee8 · outbound

This paper cites An Introduction to Convolutional Neural Networks.

Dense360: Dense Understanding from Omnidirectional Panoramas An Introduction to Convolutional Neural Networks

Reference 50

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Source-reported events for the cited work

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Observation 47526b45-8e6b-4b24-8631-4108932ab791 · outbound

This paper cites High quality entity segmentation.

Dense360: Dense Understanding from Omnidirectional Panoramas High quality entity segmentation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.734231Z

Source-reported events for the cited work

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Observation 82e57bbf-af03-49af-a59a-576f28a08b57 · outbound

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

Dense360: Dense Understanding from Omnidirectional Panoramas Learning transferable visual models from natural language supervision

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.710884Z

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Observation 16915555-55e8-4406-84dc-2fad6b5f7017 · outbound

This paper cites Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts.

Dense360: Dense Understanding from Omnidirectional Panoramas Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:53.436448Z

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Observation 4a69c100-f78b-4d77-88fc-5206b824bf2c · outbound

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

Dense360: Dense Understanding from Omnidirectional Panoramas SAM 2: Segment Anything in Images and Videos

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:53.585080Z

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Observation d40654ca-0611-45ba-8c78-d690038f1af3 · outbound

This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

Dense360: Dense Understanding from Omnidirectional Panoramas VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:53.692384Z

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Observation ffd08af7-a2be-4f06-a53c-f2575d90bbf2 · outbound

This paper cites Aligning and prompting everything all at once for universal visual perception.

Dense360: Dense Understanding from Omnidirectional Panoramas Aligning and prompting everything all at once for universal visual perception

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.684535Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71fbd254-0612-44e7-9186-24547cdd9c54 · outbound

This paper cites Long-vita: Scaling large multi-modal models to 1 million tokens with leading short-context accuray.arXiv preprint arXiv:2502.05177, 2025.

Dense360: Dense Understanding from Omnidirectional Panoramas Long-vita: Scaling large multi-modal models to 1 million tokens with leading short-context accuray.arXiv preprint arXiv:2502.05177, 2025

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:53.980985Z

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Observation 2d39abe6-e400-4315-a46a-5c563ab7bc06 · outbound

This paper cites Llm-seg: Bridging image segmentation and large language model reasoning.

Dense360: Dense Understanding from Omnidirectional Panoramas Llm-seg: Bridging image segmentation and large language model reasoning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.652859Z

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Observation 9e378ce9-5d95-4054-8433-31c0a9f585a8 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Dense360: Dense Understanding from Omnidirectional Panoramas Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:54.265144Z

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Observation 3f8391c1-75ce-496a-a048-0f143d873dc1 · outbound

This paper cites Controlmllm: Training-free visual prompt learning for multimodal large language models.NeurIPS, 2024.

Dense360: Dense Understanding from Omnidirectional Panoramas Controlmllm: Training-free visual prompt learning for multimodal large language models.NeurIPS, 2024

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.620952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 34c78318-8f09-46bd-994b-015e52c18e57 · outbound

This paper cites Panovos: Bridging non-panoramic and panoramic views with transformer for video segmentation.

Dense360: Dense Understanding from Omnidirectional Panoramas Panovos: Bridging non-panoramic and panoramic views with transformer for video segmentation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.596862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8972a759-18e8-4894-99fd-4fe916f4e0db · outbound

This paper cites Qwen2.5 Technical Report.

Dense360: Dense Understanding from Omnidirectional Panoramas Qwen2.5 Technical Report

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:54.624746Z

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Observation df891802-a942-4599-8474-fd00f7d01ca3 · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

Dense360: Dense Understanding from Omnidirectional Panoramas The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:54.745062Z

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Observation c77a6607-6fb8-4ee6-af3f-6299d34646c1 · outbound

This paper cites Lavt: Language- aware vision transformer for referring image segmentation.

Dense360: Dense Understanding from Omnidirectional Panoramas Lavt: Language- aware vision transformer for referring image segmentation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.577139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c3b87611-1e56-4280-92a5-26ad3a39d9fe · outbound

This paper cites Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos.

Dense360: Dense Understanding from Omnidirectional Panoramas Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:55.038493Z

Source-reported events for the cited work

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Observation 1b3bd26b-2507-4633-8ae5-07bba7d6b1f6 · outbound

This paper cites 4th PVUW MeViS 3rd Place Report: Sa2VA.

Dense360: Dense Understanding from Omnidirectional Panoramas 4th PVUW MeViS 3rd Place Report: Sa2VA

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:56.620076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ad2ed5a-b432-4577-824e-91ff16561e7e · outbound

This paper cites A survey of autonomous driving: Common practices and emerging technologies.

Dense360: Dense Understanding from Omnidirectional Panoramas A survey of autonomous driving: Common practices and emerging technologies

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.556252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0fba62ea-e0c4-4e14-ba15-9b393f6d363d · outbound

This paper cites Clip2: Contrastive language-image-point pretraining from real-world point cloud data.

Dense360: Dense Understanding from Omnidirectional Panoramas Clip2: Contrastive language-image-point pretraining from real-world point cloud data

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.526171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f49336c0-18ca-48ea-bd2c-df8b99664fc8 · outbound

This paper cites Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation.

Dense360: Dense Understanding from Omnidirectional Panoramas Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:55.610434Z

Source-reported events for the cited work

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Observation 4b7c6e32-ed8d-4597-a3cd-3ebc49e99a1d · outbound

This paper cites Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding.

Dense360: Dense Understanding from Omnidirectional Panoramas Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.489587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b399ce0c-bec0-4a01-8791-97bb3e3cc2dc · outbound

This paper cites Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding.

Dense360: Dense Understanding from Omnidirectional Panoramas Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:55.688403Z

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Observation 80fe0a69-10a9-445c-9a5b-6d76474da871 · outbound

This paper cites Dvis: Decoupled video instance segmentation framework.

Dense360: Dense Understanding from Omnidirectional Panoramas Dvis: Decoupled video instance segmentation framework

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.456402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e2f16be-02c8-49e2-b481-e10ad9010d02 · outbound

This paper cites Dvis++: Improved decoupled framework for universal video segmentation.

Dense360: Dense Understanding from Omnidirectional Panoramas Dvis++: Improved decoupled framework for universal video segmentation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.378499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 40febfed-cfd1-45df-b202-9a1c71f8ff8a · outbound

This paper cites Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs.

Dense360: Dense Understanding from Omnidirectional Panoramas Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:55.899256Z

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Observation 68687a91-09d6-46c1-95ab-02c4b0728478 · outbound

This paper cites Enhancing multimodal large language models complex reason via similarity computation.

Dense360: Dense Understanding from Omnidirectional Panoramas Enhancing multimodal large language models complex reason via similarity computation

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.255336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7dcf37e0-b583-4232-8626-40ffb3a89a85 · outbound

This paper cites Regionclip: Region-based language-image pretraining.

Dense360: Dense Understanding from Omnidirectional Panoramas Regionclip: Region-based language-image pretraining

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:12.136861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e8acef3b-10fd-4b4c-82dd-6acd6bf68b49 · outbound

This paper cites Improving video segmentation via dynamic anchor queries.

Dense360: Dense Understanding from Omnidirectional Panoramas Improving video segmentation via dynamic anchor queries

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:24:11.979969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd2f3850-3373-487a-b4ea-3993548ed273 · outbound

This paper cites Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs.

Dense360: Dense Understanding from Omnidirectional Panoramas Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:56.252708Z

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Observation 12a90f74-4402-4da3-8371-388257d89423 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Dense360: Dense Understanding from Omnidirectional Panoramas InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:56.322623Z

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Pith citing papers

Observation 1b5bdbbc-14f6-4d15-b26f-aa9dc18a1628 · inbound

PanoWorld: Towards Spatial Supersensing in 360$^\circ$ Panorama World cites this paper.

PanoWorld: Towards Spatial Supersensing in 360$^\circ$ Panorama World Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:42:57.567508Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d18b3c03-058f-4fb2-b7ce-a6613df24e78 · inbound

PanoWorld: Towards Spatial Supersensing in 360$^\circ$ Panorama World cites this paper.

PanoWorld: Towards Spatial Supersensing in 360$^\circ$ Panorama World Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:57:40.064154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3ab9d8fd-0a07-4b9b-96e7-967f7a35d735 · inbound

Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling cites this paper.

Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 141

Resolution: verified exact; arxiv_id, observed 2026-06-29T20:03:56.656459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 54ee12cd-47b0-4a95-b8db-ccb515c3969f · inbound

Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling cites this paper.

Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 137

Resolution: unresolved; no resolver link, observed 2026-08-02T09:59:02.378826Z

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Observation f8fe511e-517b-4919-84df-b8aaffa6e0ba · inbound

OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning cites this paper.

OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 52

Resolution: malformed identifier; arxiv_id, observed 2026-06-30T06:14:19.099103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5a7cc748-3773-4ead-af02-2aebbaf69429 · inbound

Seek to Segment: Active Perception for Panoramic Referring Segmentation cites this paper.

Seek to Segment: Active Perception for Panoramic Referring Segmentation Dense360: Dense Understanding from Omnidirectional Panoramas

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:48:32.616438Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.