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Paper Citation Record · LEDGER

Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2503.22679.

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

pith.paper-citation-record.v1
2503.22679 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:12:18.291355Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3ba3d510-4fc2-434d-8873-47a75d0e3519 · inbound

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models cites this paper.

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 47

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no resolver link, observed 2026-08-16T05:12:18.291355Z

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source=pdf_text observed=2026-08-16T05:12:18.291355Z digest=sha256:502587e34538b7067b88357c8a7202386851878eb44780f50fe9e8c15a28588a

Observation 496011d8-4e0b-4c11-b078-090c603f2b73 · inbound

Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models cites this paper.

Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 87

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source=pdf_text observed=2026-08-07T14:31:16.030204Z digest=sha256:473b1db3fbf41df5ddd2b4dc63cddfd25e9aa38324b010ad4b016cc0a09e91a1

Observation 6c8b85b2-4ba2-4ead-9039-fa2ec3d732cb · inbound

MIND-Edit: MLLM Insight-Driven Editing via Language-Vision Projection cites this paper.

MIND-Edit: MLLM Insight-Driven Editing via Language-Vision Projection Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 27

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source=pdf_text observed=2026-08-07T14:23:07.552002Z digest=sha256:2a7eee93ca511b88de8a9f64f350e8bce203875ed6308afbfb220952ad3e026d

Observation 0ad260c2-d174-44dd-bcf9-4f09ac66a99c · inbound

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models cites this paper.

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 14

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no resolver link, observed 2026-08-07T14:51:32.282841Z

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source=pdf_text observed=2026-08-07T14:51:32.282841Z digest=sha256:956465dd6f3d9eddd4585395b5ef3267abd50617835f8aa5a06b7a738de1d2e4

Observation af69b475-a00a-4cc2-8388-fb419e9b0713 · inbound

Q-Ponder: A Unified Training Pipeline for Reasoning-based Visual Quality Assessment cites this paper.

Q-Ponder: A Unified Training Pipeline for Reasoning-based Visual Quality Assessment Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 24

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source=pdf_text observed=2026-08-07T11:22:44.700327Z digest=sha256:a53e679e7c12f7b7cb6901e7d32300eada6da07f398ab4e0324dd10eacb4196b

Observation 5905a557-fd8a-45c3-9c65-19082bcbc31a · inbound

VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning cites this paper.

VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 19

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no resolver link, observed 2026-08-06T23:20:47.854754Z

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source=arxiv_source observed=2026-08-06T23:20:47.854754Z digest=sha256:795845bfd1fd6d8742be5b09e458edb1d4d12b3ce5f8e66b28f5348ff953f23b

Observation 6ea83512-903b-46b3-a112-1061ddb4d6b9 · inbound

Flow reorganization and transport enhancement in two-dimensional horizontal convection near a density extremum cites this paper.

Flow reorganization and transport enhancement in two-dimensional horizontal convection near a density extremum Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-15T17:29:22.204366Z

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source=pdf_text observed=2026-08-15T17:29:22.204366Z digest=sha256:8f15c09bed25dac9a2657a7c368bb51b3672110a0989a95073cbd1a64ee751c7

Observation 3d0669fa-2b42-431f-981e-a1fe5d9559bc · inbound

RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts cites this paper.

RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-15T17:25:47.910716Z

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source=arxiv_source observed=2026-08-15T17:25:47.910716Z digest=sha256:8437b73fb8170f314fa53681fd8b3689cce416460cb72cb12222f9ab0c4f1140

Observation 69609d4e-bbe0-4068-bba3-cd85511dc64f · inbound

Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoning cites this paper.

Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoning Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 11

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source=pdf_text observed=2026-08-15T17:28:25.548413Z digest=sha256:e8c6dbbb616d812ed30e04036d7068f609a1905b40d9d78cd8cfbe30a2903c5f

Observation 672062f7-eb0a-44f8-88fc-11d69b0ad0f5 · inbound

VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results cites this paper.

VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 26

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source=pdf_text observed=2026-08-04T19:34:24.909889Z digest=sha256:4ed8798af49a6c5fe190c331a738305a690950a5ef7bdb9cba6e3273f9b0c91e

Observation 7f6bd7f3-9aea-4cae-a0e1-a6bfa50a62bd · inbound

EmoFeedback$^2$: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback cites this paper.

EmoFeedback$^2$: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 2024

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source=pdf_text observed=2026-08-03T20:26:25.814260Z digest=sha256:31df6c544c7a6130fb632d1f94b21d41c237bb33e49fd6319faf14ce031008ac

Observation 8013f432-c8e3-48fe-98c4-bb80e7e7d9f9 · inbound

Zoom-IQA: Image Quality Assessment with Reliable Region-Aware Reasoning cites this paper.

Zoom-IQA: Image Quality Assessment with Reliable Region-Aware Reasoning Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 29

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source=pdf_text observed=2026-08-03T12:31:14.886253Z digest=sha256:aec9b8af77e59f66c5f920e98faa33d10fb2b7e1142cd7b3a8649170fbdada7a

Observation 917b70c7-d53c-472a-aa29-24e9ed0bf0cf · inbound

Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing cites this paper.

Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 7

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arxiv_id, observed 2026-05-16T12:47:54.137660Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 235ff2aa-009b-40b4-b299-f1c65d14a45b · inbound

ME-IQA: Memory-Enhanced Image Quality Assessment via Re-Ranking cites this paper.

ME-IQA: Memory-Enhanced Image Quality Assessment via Re-Ranking Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 25

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source=pdf_text observed=2026-08-02T17:49:56.113643Z digest=sha256:151eecebdf78ea95ecc401379fcf0a5c7c7d1d31e59105dba39ae07598d4d1fa

Observation aa916beb-3abe-4daf-a106-48ca6ea83554 · inbound

Panoptic Pairwise Distortion Graph cites this paper.

Panoptic Pairwise Distortion Graph Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 1

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arxiv_id, observed 2026-05-11T10:46:06.402528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T15:18:40.004349Z digest=sha256:90b4228c27bf8a3b2b000b6908e1017dfa4f948e5f29c87399fcb4b4e240ac54

Observation 71dc94c9-fe45-46a5-8495-a90213221222 · inbound

Q-DeepSight: Incentivizing Thinking with Images for Image Quality Assessment and Refinement cites this paper.

Q-DeepSight: Incentivizing Thinking with Images for Image Quality Assessment and Refinement Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 22

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arxiv_id, observed 2026-05-10T06:46:37.254247Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T06:43:54.201604Z digest=sha256:ac864c754041983743299279da84c0fab0fe82ed987eaa9f6e1269e0056e7d9f

Observation 65a3a87b-8ce1-47c0-9a2b-687889ffd370 · inbound

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression cites this paper.

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 20

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arxiv_id, observed 2026-05-11T16:51:09.324004Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-09T14:36:29.666730Z digest=sha256:9d42e59ff9e5841fabd387c0c9a39936da6c62ae6f129ab873734804bd6f5ba0

Observation 40f2154d-fc9f-4735-a63a-fbdb63dabd22 · inbound

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression cites this paper.

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 20

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arxiv_id, observed 2026-05-12T05:51:26.175599Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T04:52:09.685243Z digest=sha256:8e64d0091512629b1252fe0b6d377142581436d2b0b54ecd1c8483ee1507c81b

Observation 2343188c-48ca-4ecc-bf50-27e705477018 · inbound

RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition cites this paper.

RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 76

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arxiv_id, observed 2026-05-13T07:47:31.025282Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-13T07:46:50.540528Z digest=sha256:9f1a8d878991b3554bd5755b07aa56c452cbc23b0c187c3f4297c023539b5847

Observation 9f739254-75a9-4dd2-b2f4-5f3dc42d5790 · inbound

Ultra-High-Definition Image Quality Assessment via Graph Representation Learning cites this paper.

Ultra-High-Definition Image Quality Assessment via Graph Representation Learning Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 26

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arxiv_id, observed 2026-05-22T08:04:42.640087Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 41f4957f-a65f-4b89-8c64-1b8c8bdde2a4 · inbound

DRM: Diffusion-based Reward Model With Step-wise Guidance cites this paper.

DRM: Diffusion-based Reward Model With Step-wise Guidance Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 17

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arxiv_id, observed 2026-06-29T22:13:59.396569Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T22:12:39.225557Z digest=sha256:03b2578278068fbf4973075b74286746fd7e4d110d2e90732c27d6d9fdf83b16

Observation 06b42fef-5ab1-494a-9a64-46e9fea1a965 · inbound

HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution cites this paper.

HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 17

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arxiv_id, observed 2026-07-01T21:06:13.470541Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-28T17:32:15.239191Z digest=sha256:22450bb79af290d6f40889ed474df62874dede83907ad4cde1c6e95e4a57aacf

Observation c1d44f09-0543-4e29-a748-9303b2e40758 · 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 Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 26

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arxiv_id, observed 2026-07-02T12:06:55.932789Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 0aab4778-dd7a-41af-bd0c-9b6feb59efcc · 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 Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 26

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arxiv_id, observed 2026-06-30T11:14:37.674771Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:11:21.975534Z digest=sha256:8b029aa8c2e5dd530a80e2dffed1086abc701748b0eb7d39be96a16675b89ceb

Observation 283bea3c-32c0-4ee7-81b7-fe4e1da2dfaf · inbound

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment cites this paper.

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 20

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source=pdf_text observed=2026-08-02T03:19:52.579696Z digest=sha256:166472de4727c4ba23c00a0ff1ab7bfc8e8f72f5113c872577a8080c13005e09

Observation 52578dff-6c6b-4f09-a199-1c36788f82a5 · inbound

COMEX: A Composition-Grounded Benchmark and Learning Framework for Explainable Aesthetic Image Cropping cites this paper.

COMEX: A Composition-Grounded Benchmark and Learning Framework for Explainable Aesthetic Image Cropping Q-Insight: Understanding Image Quality via Visual Reinforcement Learning

Reference 28

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