Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:59:13.873750Z
Paper Citation Record · LEDGER
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 18 inbound Pith citation observations for arXiv:2507.14533.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T20:52:35.731610Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
43 of 43 outbound references displayed
- verified exact5
- verified fuzzy21
- unresolved14
- parse uncertain0
- malformed identifier0
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External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 5e183f1f-b136-49d9-90c4-0aa29d0446ab · outbound
This paper cites Dreamlike photoreal 2.0,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Dreamlike photoreal 2.0,
Reference 1
- Resolution
- verified fuzzy
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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 56a6793d-3ebd-4b23-8b1d-7a83d695a0fd · outbound
This paper cites an unresolved cited work.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Unresolved cited work
Reference 2
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f39c693f-a439-4277-8979-62495f7c991f · outbound
This paper cites High-resolution image synthesis with latent diffusion models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding High-resolution image synthesis with latent diffusion models,
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb9841c5-e136-4d85-acba-185a87749f78 · outbound
This paper cites Depicting beyond scores: Advancing image quality assessment through multi-modal language models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Depicting beyond scores: Advancing image quality assessment through multi-modal language models,
Reference 4
- Resolution
- verified fuzzy
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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 d649d85e-755e-40c5-8454-272e870c2e74 · outbound
This paper cites Descriptive image quality assessment in the wild,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Descriptive image quality assessment in the wild,
Reference 5
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f73dc1a-4778-4c56-a2ac-fad984817f37 · outbound
This paper cites Teaching large language models to regress accurate image quality scores using score distribution,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Teaching large language models to regress accurate image quality scores using score distribution,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:59:16.328118Z
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 f240f694-6d4d-4b86-9629-e39c093e8beb · outbound
This paper cites AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception
Reference 7
- Resolution
- verified exact
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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 125b3a56-2a34-4955-896f-fdd9cdb98988 · outbound
This paper cites Aesmamba: Universal image aesthetic assessment with state space models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Aesmamba: Universal image aesthetic assessment with state space models,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:59:16.301403Z
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 21631b23-9811-4a27-a584-14a61e39ac43 · outbound
This paper cites APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:59:15.323746Z
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 c14a9f04-0e2e-485b-bf2f-1e29dee5938d · outbound
This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Reference 10
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41e1b680-9f79-4b6b-be9c-464fd3581474 · outbound
This paper cites Qwen2.5-VL Technical Report.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Qwen2.5-VL Technical Report
Reference 11
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 917eaa9b-2e8f-4115-a901-908df8605483 · outbound
This paper cites Q-align: Teaching LMMs for visual scoring via discrete text-defined levels,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Q-align: Teaching LMMs for visual scoring via discrete text-defined levels,
Reference 12
- Resolution
- verified fuzzy
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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 0513be77-9a8c-4a73-b50d-b54ed0c90a33 · outbound
This paper cites GPT-4 Technical Report.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding GPT-4 Technical Report
Reference 13
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9db0f55d-3ea9-4795-b440-270b183a92d7 · outbound
This paper cites Gemini: A Family of Highly Capable Multimodal Models.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Gemini: A Family of Highly Capable Multimodal Models
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00b261c0-26a1-4216-8bb3-b94a258ecabc · outbound
This paper cites Rethinking image aesthetics assessment: Models, datasets and benchmarks,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Rethinking image aesthetics assessment: Models, datasets and benchmarks,
Reference 15
- Resolution
- verified fuzzy
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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 2daf35e8-6ff4-435e-9d7f-78a7ba62f39a · outbound
This paper cites Photo Aesthetics Ranking Network with Attributes and Content Adaptation.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Reference 16
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eebcd885-0398-4c2d-a7f9-409312921335 · outbound
This paper cites Personalized Image Aesthetics Assessment with Rich Attributes.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Personalized Image Aesthetics Assessment with Rich Attributes
Reference 17
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e87294b5-662e-4d36-9320-cd1ee5755fac · outbound
This paper cites Ava: A large-scale database for aesthetic visual analysis,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Ava: A large-scale database for aesthetic visual analysis,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:59:16.224782Z
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 c6fc9707-0096-4d4c-ae49-98633edf98b5 · outbound
This paper cites ArtEmis: Affective Language for Visual Art.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding ArtEmis: Affective Language for Visual Art
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2e6a027-f3fd-463f-beaf-b5f711646b20 · outbound
This paper cites Impressions: Understanding visual semiotics and aesthetic impact,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Impressions: Understanding visual semiotics and aesthetic impact,
Reference 20
- Resolution
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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 e30ce7f0-a769-49a8-9c42-f588e48485dd · outbound
This paper cites Understanding aesthetics with language: A photo critique dataset for aesthetic assessment,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Understanding aesthetics with language: A photo critique dataset for aesthetic assessment,
Reference 21
- Resolution
- verified fuzzy
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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 89be8dc4-9c5b-4b6c-a94e-ae850742ed87 · outbound
This paper cites Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method
Reference 22
- Resolution
- verified exact
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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 016eccef-a26c-4581-b9e6-efb827d26ac4 · outbound
This paper cites Q- instruct: Improving low-level visual abilities for multi-modality foundation models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Q- instruct: Improving low-level visual abilities for multi-modality foundation models,
Reference 23
- Resolution
- verified fuzzy
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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 8d7fb08d-abc2-4331-958c-d251d37fdb36 · outbound
This paper cites Scaling up personalized image aesthetic assessment via task vector customization,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Scaling up personalized image aesthetic assessment via task vector customization,
Reference 24
- Resolution
- verified fuzzy
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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 23a7be91-a06c-46db-9121-6dd6f6da7605 · outbound
This paper cites UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmark.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmark
Reference 25
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49fec351-b51e-4997-8c25-48c9340ffee0 · outbound
This paper cites Personalized image aesthetics,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Personalized image aesthetics,
Reference 26
- Resolution
- verified fuzzy
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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 6cc06fd7-a893-455a-bbe0-9258a30ab5ac · outbound
This paper cites Perceptual quality assessment of smartphone photography,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Perceptual quality assessment of smartphone photography,
Reference 27
- Resolution
- verified fuzzy
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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 4182e76e-1e27-49b3-a503-bad6218ba300 · outbound
This paper cites Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment,
Reference 28
- Resolution
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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 838c3c2b-9449-432c-9425-2da1b95f6aae · outbound
This paper cites Grids: Grouped multiple-degradation restoration with image degradation similarity,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Grids: Grouped multiple-degradation restoration with image degradation similarity,
Reference 29
- Resolution
- verified fuzzy
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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 cc809acf-4257-4aea-8a47-b8ca619f27ba · outbound
This paper cites Diffvsr: Enhancing real- world video super-resolution with diffusion models for advanced visual quality and temporal consistency,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Diffvsr: Enhancing real- world video super-resolution with diffusion models for advanced visual quality and temporal consistency,
Reference 30
- Resolution
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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 44c1817f-8631-4df0-9c02-5392ae613638 · outbound
This paper cites DualX-VSR: Dual Axial Spatial$\times$Temporal Transformer for Real-World Video Super-Resolution without Motion Compensation.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding DualX-VSR: Dual Axial Spatial$\times$Temporal Transformer for Real-World Video Super-Resolution without Motion Compensation
Reference 31
- Resolution
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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 c8b60c04-808c-4d60-9567-f8133c78a1f2 · outbound
This paper cites Language models are unsupervised multitask learners,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Language models are unsupervised multitask learners,
Reference 32
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bed15cc9-0ce9-4f22-893b-b82194b6718e · outbound
This paper cites Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language Model.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language Model
Reference 33
- Resolution
- verified exact
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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 ab42ed88-943f-480b-9b22-2290fd2b7407 · outbound
This paper cites Sgdr: Stochastic gradient descent with warm restarts,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Sgdr: Stochastic gradient descent with warm restarts,
Reference 34
- Resolution
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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 6d18a0ff-1c08-4dc9-bcdb-830242f76c29 · outbound
This paper cites MUSIQ: Multi-scale Image Quality Transformer.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding MUSIQ: Multi-scale Image Quality Transformer
Reference 35
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c458c67-0c2f-47a3-a0da-08692ef49642 · outbound
This paper cites Vila: On pre-training for visual language models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Vila: On pre-training for visual language models,
Reference 36
- Resolution
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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 e14b73ba-1a72-4346-b983-a6787f278889 · outbound
This paper cites mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration
Reference 37
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 470f13e7-81c2-4a4c-b948-4bd7515161aa · outbound
This paper cites Sharegpt4v: Improving large multi-modal models with better captions,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Sharegpt4v: Improving large multi-modal models with better captions,
Reference 38
- Resolution
- verified fuzzy
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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 7ceb9573-f842-4f24-995e-594c74305016 · outbound
This paper cites Q-instruct: Improving low-level visual abilities for multi-modality foundation models,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Q-instruct: Improving low-level visual abilities for multi-modality foundation models,
Reference 39
- Resolution
- verified fuzzy
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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 aecd69a7-b3f7-4913-b787-5d45ba69fe73 · outbound
This paper cites Scaling up personalized image aesthetic assessment via task vector customization,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Scaling up personalized image aesthetic assessment via task vector customization,
Reference 40
- Resolution
- verified fuzzy
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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 304e81e6-d726-440b-9080-6ff91386f8e9 · outbound
This paper cites Methodology for the subjective assessment of the quality of television pictures,.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Methodology for the subjective assessment of the quality of television pictures,
Reference 41
- Resolution
- verified fuzzy
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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 57a946ad-e2c0-4bf3-901a-a8510c67b9b9 · outbound
This paper cites Impressions: Understanding Visual Semiotics and Aesthetic Impact.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Impressions: Understanding Visual Semiotics and Aesthetic Impact
Reference 2023
- Resolution
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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 928cd6f2-ede2-4c8f-9cb0-dd34a9ecabed · outbound
This paper cites Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization.
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization
Reference 2024
- Resolution
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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.
Pith citing papers
Observation 671aea1a-f4ef-41a1-9db8-31bde2be871a · inbound
UltraFlux: Data-Model Co-Design for High-quality Native 4K Text-to-Image Generation across Diverse Aspect Ratios cites this paper.
UltraFlux: Data-Model Co-Design for High-quality Native 4K Text-to-Image Generation across Diverse Aspect Ratios ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d09739e-5f38-4ff2-9f6a-99d98c8a75a5 · inbound
PhotoFramer: Multi-modal Image Composition Instruction cites this paper.
PhotoFramer: Multi-modal Image Composition Instruction ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 4
- Resolution
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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 9b50e4ae-fe06-488c-847c-e0582dcc3693 · inbound
PortraitCraft: A Benchmark for Portrait Composition Understanding and Generation cites this paper.
PortraitCraft: A Benchmark for Portrait Composition Understanding and Generation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 2
- Resolution
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- arxiv_id, observed 2026-05-13T18:18:06.362355Z
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 9e6cf156-74b8-4c99-b182-b674424bbc64 · inbound
On Semiotic-Grounded Interpretive Evaluation of Generative Art cites this paper.
On Semiotic-Grounded Interpretive Evaluation of Generative Art ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:20:52.749062Z
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 873dd750-cbad-4ec8-9d21-8725698b68c0 · inbound
Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation cites this paper.
Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T06:41:36.480157Z
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 32dd2f2c-8bf2-4fbd-8094-1104d58424b2 · inbound
UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement cites this paper.
UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:33:41.725718Z
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 356576fb-a2d0-4cd4-bfc1-4bd9266d09e4 · inbound
LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model cites this paper.
LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T00:49:48.317459Z
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 ff175dce-0067-4456-8563-c0112fe58375 · inbound
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation cites this paper.
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:55:43.721058Z
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 d14a179a-f6a1-4277-acc1-ad0bbe483241 · inbound
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation cites this paper.
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T08:19:52.717102Z
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 007d6372-7261-4a07-a24b-54cc4a1ea7f5 · inbound
DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models cites this paper.
DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:46:10.561238Z
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 ecafff88-7b4d-4573-99ce-14f41da29d33 · inbound
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation cites this paper.
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T06:58:05.784768Z
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 a65e7dfb-b17f-40f7-8d1f-bf365efb5c9f · inbound
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation cites this paper.
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T07:29:48.193391Z
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 d0d551a4-5e6c-4a0a-8c26-2ab93afe2ece · inbound
PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset cites this paper.
PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T05:23:03.851637Z
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 bc1c431d-ecd7-44e1-a4a4-911433900bfb · inbound
AesFormer: Transform Everyday Photos into Beautiful Memories cites this paper.
AesFormer: Transform Everyday Photos into Beautiful Memories ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T07:11:12.728305Z
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 49d38ac9-7316-4aaf-8690-9610bcf7e1d4 · inbound
VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset cites this paper.
VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:25:19.702211Z
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 5f9c9884-1d17-46b7-8fa3-2ad20bc015f7 · inbound
DRM: Diffusion-based Reward Model With Step-wise Guidance cites this paper.
DRM: Diffusion-based Reward Model With Step-wise Guidance ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T22:13:59.409644Z
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 1ca82cc1-6506-41dc-924d-19100a5b4c2d · inbound
Beyond Absolute Scores: Relative Edit-induced Difference for Generalizable Image Aesthetic Assessment cites this paper.
Beyond Absolute Scores: Relative Edit-induced Difference for Generalizable Image Aesthetic Assessment ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T12:06:55.911195Z
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 2304d26d-0903-4359-a0e3-2dbbd92d0b42 · inbound
Beyond Absolute Scores: Relative Edit-induced Difference for Generalizable Image Aesthetic Assessment cites this paper.
Beyond Absolute Scores: Relative Edit-induced Difference for Generalizable Image Aesthetic Assessment ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T11:14:37.686198Z
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.