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Paper Citation Record · LEDGER

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining

As of 11 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.08765.

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

pith.paper-citation-record.v1
2607.08765 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T15:29:14.328745Z

measured 26 of 26 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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Outbound references

Observation b5a99d9a-d9e6-49bd-a287-8f5a9a8c7dd8 · outbound

This paper cites Qwen3-VL Technical Report.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Qwen3-VL Technical Report

Reference 1

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:4bfc3aa6dc97b8feec32cf1147c8fa84e06cf64b6b1dc3e56fbd41e448592394

Observation 641a5f36-da02-4e81-ab43-97e94b3baf92 · outbound

This paper cites Loosecontrol: Lifting controlnet for generalized depth conditioning.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Loosecontrol: Lifting controlnet for generalized depth conditioning

Reference 2

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Observation 9d8e7c98-39d3-42fa-848f-a1dba4c639b8 · outbound

This paper cites Black Forest Labs.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Black Forest Labs

Reference 3

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:f53bab2c98d348dbac15c82fda78d9e95a4e596449171d97f4557722587b79bd

Observation 1b48b7ad-7540-4d41-97e2-56b41b29b817 · outbound

This paper cites Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang

Reference 4

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:192971a2866e16a272488eac4901587d304edc470ea2fb9e83e85659ccae5943

Observation ab905c23-9f22-48ca-b4d1-828c341277f1 · outbound

This paper cites Hao Chen, Yuqi Hou, Chenyuan Qu, Irene Testini, Xiaohan Hong, and Jianbo Jiao.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Hao Chen, Yuqi Hou, Chenyuan Qu, Irene Testini, Xiaohan Hong, and Jianbo Jiao

Reference 5

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:7332c53670d8e36776f98512464ec71228f0badde1e10bedf10818e42a852030

Observation bd1a9969-48e5-4093-b1d3-68ba4edf874e · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Emerging Properties in Unified Multimodal Pretraining

Reference 6

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:bbacd4d083c3412e9d255586b712462310bf82aa53f6cee7fdaa758611675485

Observation 529699de-0d43-41b8-b5ee-be715c145614 · outbound

This paper cites Dit360: High-fidelity panoramic image generation via hybrid training.arXiv preprint arXiv:2510.11712,.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Dit360: High-fidelity panoramic image generation via hybrid training.arXiv preprint arXiv:2510.11712,

Reference 7

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:d920d38c85e37d1ba4eef5b8a0eac50206cf0ed68a8c1d289359cb2f26bfaf83

Observation 8f19c390-12e1-4de0-8e60-04760d185ea7 · outbound

This paper cites Mean Flows for One-step Generative Modeling.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Mean Flows for One-step Generative Modeling

Reference 8

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Observation 7ffa78f0-b589-4b60-8c95-4d9b7749f2ef · outbound

This paper cites Nano banana.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Nano banana

Reference 9

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Observation 9547670e-23e1-4f51-906e-b05a008a9039 · outbound

This paper cites Unityvideo: Unified multi-modal multi-task learning for enhancing world-aware video generation.arXiv preprint arXiv:2512.07831, 2025a.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Unityvideo: Unified multi-modal multi-task learning for enhancing world-aware video generation.arXiv preprint arXiv:2512.07831, 2025a

Reference 10

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Observation a30e540a-bdb3-428b-b2c3-38d85fbabc91 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 11

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Observation 0bfaa171-341d-4a84-a3f1-8126741a3810 · outbound

This paper cites Thinking with camera: A unified multimodal model for camera-centric understanding and generation.arXiv preprint arXiv:2510.08673,.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Thinking with camera: A unified multimodal model for camera-centric understanding and generation.arXiv preprint arXiv:2510.08673,

Reference 12

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Observation 1dc7cf5c-5453-4023-8983-d88914eab23f · outbound

This paper cites Depth any panoramas: A foundation model for panoramic depth estimation.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Depth any panoramas: A foundation model for panoramic depth estimation

Reference 13

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Observation 8ed9fc5e-fb51-4af5-a36a-f67c00fb9273 · outbound

This paper cites Flow Matching for Generative Modeling.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Flow Matching for Generative Modeling

Reference 14

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Observation 202e2816-caa6-4cc4-b25c-8f45a1e32562 · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Step1X-Edit: A Practical Framework for General Image Editing

Reference 15

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source=pdf_text observed=2026-07-14T15:29:14.328745Z digest=sha256:3fc56f8e7e59338190894428afdf0365e7bb6e5c48128a9763a8ca9f2ad4f471

Observation 3aecc7fb-7f55-40b9-a3c8-2891b4380313 · outbound

This paper cites Minho Park, Taewoong Kang, Jooyeol Yun, Sungwon Hwang, and Jaegul Choo.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Minho Park, Taewoong Kang, Jooyeol Yun, Sungwon Hwang, and Jaegul Choo

Reference 16

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Observation b4a3007e-0e4b-4fcb-9a7d-e8088f91ab30 · outbound

This paper cites Masked depth modeling for spatial perception.arXiv preprint arXiv:2601.17895,.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Masked depth modeling for spatial perception.arXiv preprint arXiv:2601.17895,

Reference 17

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Observation e642d2bb-8430-4ad3-ac04-e871e5b3f240 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Wan: Open and Advanced Large-Scale Video Generative Models

Reference 18

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Observation 99c72666-a016-4009-a436-18496c91dd25 · outbound

This paper cites OmniGen2: Towards Instruction-Aligned Multimodal Generation.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining OmniGen2: Towards Instruction-Aligned Multimodal Generation

Reference 19

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Observation a5f93c06-e9d7-494b-a586-a40b9851fd21 · outbound

This paper cites JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling

Reference 20

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Observation c15c7cc7-11bd-4ec9-bf32-6fd614e8e832 · outbound

This paper cites Inversion-based style transfer with diffusion models.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Inversion-based style transfer with diffusion models

Reference 21

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Observation fd4c6384-ad65-406f-aaa9-c97bbdd11f02 · outbound

This paper cites In contrast, the model trained with depth supervision produces more coherent depth structures and better cross-view consistency.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining In contrast, the model trained with depth supervision produces more coherent depth structures and better cross-view consistency

Reference 22

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Observation 40a4818f-a6bd-4019-8a62-77ffa7883c60 · outbound

This paper cites Oscillatory processes in solar flares.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Oscillatory processes in solar flares

Reference 23

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Observation 5510b9c9-8d03-4293-8ce5-25c7c7039396 · outbound

This paper cites an unresolved cited work.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Unresolved cited work

Reference 24

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Observation d62b75f5-b481-40fa-97be-5aa302e5a1d9 · outbound

This paper cites We report CP (Content Preservation), SR (Style Resemblance), and OV (Overall Vision).

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining We report CP (Content Preservation), SR (Style Resemblance), and OV (Overall Vision)

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Observation 996475c3-6701-4ce9-9618-8f8b2f13ff7f · outbound

This paper cites Across both inpainting and outpainting, our method achieves the best results on all three metrics, yielding lower LPIPS and FAED as well as higher PSNR than all baselines.

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining Across both inpainting and outpainting, our method achieves the best results on all three metrics, yielding lower LPIPS and FAED as well as higher PSNR than all baselines

Reference 26

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Pith citing papers

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