Paper Citation Record · LEDGER

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning

As of 19 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 4 inbound Pith citation observations for arXiv:2411.10161.

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

pith.paper-citation-record.v1
2411.10161 v1

Coverage vector

measured 73 of 73 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:59:43.554841Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:27:52.851606Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T19:01:11.706698Z

Reference resolution

73 of 73 outbound references displayed

verified exact0
verified fuzzy50
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fccab17c-1552-4829-a6e4-3a5cf0cbd484 · outbound

This paper cites GPT-4 Technical Report.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.287191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d9d991c-4fcc-4e89-8bf2-36d60a518361 · outbound

This paper cites Quality-aware image-text alignment for real-world image quality assessment, 2024.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Quality-aware image-text alignment for real-world image quality assessment, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.451899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4362e7d9-6ea6-401d-a7e2-3b993f0db5da · outbound

This paper cites an unresolved cited work.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:59:44.440629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad61f082-8968-4f23-bbac-6b4ddf25e22b · outbound

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

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Flamingo: a visual language model for few-shot learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.299569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e29d4765-93a6-43b8-88e9-1bc2e1c5bb04 · outbound

This paper cites Topiq: A top-down approach from semantics to distortions for image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Topiq: A top-down approach from semantics to distortions for image quality assessment

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.422356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2fee339c-ea6b-4547-bfb9-936927f780b8 · outbound

This paper cites Q-Ground: Image Quality Grounding with Large Multi-modality Models.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Q-Ground: Image Quality Grounding with Large Multi-modality Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.307285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff592be-d073-4cf8-84c8-b9f86e43d948 · outbound

This paper cites Teacher-guided learning for blind image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Teacher-guided learning for blind image quality assessment

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.411235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23dd19a6-4d00-46c8-8f3b-143664f7dcdd · outbound

This paper cites Promptiqa: Boosting the performance and generalization for no-reference image quality assessment via prompts.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Promptiqa: Boosting the performance and generalization for no-reference image quality assessment via prompts

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.399639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0a62cb21-b873-403b-826a-f9ce39662c94 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.318427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f13f62c6-9a44-47f2-9e9a-6a69fd303c2f · outbound

This paper cites No-reference blur assessment of digital pictures based on multifeature classifiers.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning No-reference blur assessment of digital pictures based on multifeature classifiers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.381867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b9e76136-3f74-44b7-b646-9348715af8ef · outbound

This paper cites Instructblip: Towards general- purpose vision-language models with instruction tuning.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Instructblip: Towards general- purpose vision-language models with instruction tuning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.370746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aed93c97-1e6a-4f72-8218-0d640f8690df · outbound

This paper cites Raise: a raw images dataset for digital image forensics.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Raise: a raw images dataset for digital image forensics

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.359785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b56ac7d7-eeb9-49ff-bdab-f3afdb39a194 · outbound

This paper cites Perceptual quality assessment of smartphone photog- raphy.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Perceptual quality assessment of smartphone photog- raphy

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.335600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9005de9-07a2-4062-bb2e-4e5590428c77 · outbound

This paper cites Learn- ing to rank for blind image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Learn- ing to rank for blind image quality assessment

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.335788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5fb50403-e626-4633-8816-16a4dfaa4418 · outbound

This paper cites Reversible data hiding-based contrast en- hancement with multi-group stretching for roi of medical im- age.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Reversible data hiding-based contrast en- hancement with multi-group stretching for roi of medical im- age

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.324566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d91583c-f0b5-4e39-94ec-0d1aaaf3b68a · outbound

This paper cites Massive online crowdsourced study of subjective and objective picture qual- ity.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Massive online crowdsourced study of subjective and objective picture qual- ity

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.346669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98f98e01-9c8f-41ad-9960-26661ef51233 · outbound

This paper cites No-reference image quality assessment via transformers, rel- ative ranking, and self-consistency.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning No-reference image quality assessment via transformers, rel- ative ranking, and self-consistency

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.306353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1706a04d-fe12-43b3-ba50-2979bc6bd1ab · outbound

This paper cites Image compression using object-based regions of interest.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Image compression using object-based regions of interest

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.294449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1e30a6f5-901d-4148-994d-b2b061b1c094 · outbound

This paper cites Deep residual learning for image recognition.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Deep residual learning for image recognition

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.358507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcfccc82-627d-4e8e-8ef1-aedc517cc232 · outbound

This paper cites Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.278030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f33ea824-6d08-42bb-b446-4e6a40c263bc · outbound

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

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning LoRA: Low-Rank Adaptation of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.366055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd1e933-81e3-4e03-8d6b-91281cd3c9b3 · outbound

This paper cites Enhanced roi (region of interest algorithms) for medical image compression.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Enhanced roi (region of interest algorithms) for medical image compression

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.267164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 635068b6-3f99-448e-94ff-d232a3c813cc · outbound

This paper cites Convolu- tional neural networks for no-reference image quality assess- ment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Convolu- tional neural networks for no-reference image quality assess- ment

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.373681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdcbae2a-7391-434a-be44-3109e8a01543 · outbound

This paper cites Transformer-based variable-rate image compression with region-of-interest control.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Transformer-based variable-rate image compression with region-of-interest control

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.250209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f7b521a-e35e-45dc-b49c-8944949fdde5 · outbound

This paper cites Re- gion of interest based contrast enhancement techniques for ct images.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Re- gion of interest based contrast enhancement techniques for ct images

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.238074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 309c3c60-c55a-4623-b7b8-cee0ff35d187 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Musiq: Multi-scale image quality transformer

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.227376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 875614de-a524-49e3-a619-83aff11e346b · outbound

This paper cites Segment anything in high qual- ity.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Segment anything in high qual- ity

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.388818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88e55dbb-e056-4e1e-90d0-760037221cc9 · outbound

This paper cites As- sessment of roi selection for facial video-based rppg.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning As- sessment of roi selection for facial video-based rppg

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.209033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1cbf9822-0863-481d-9845-0dff462e479c · outbound

This paper cites As- sessment of roi selection for facial video-based rppg.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning As- sessment of roi selection for facial video-based rppg

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.197088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e603752-10c9-4051-9044-f27019ea1732 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.185174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7de10502-e66e-4a75-8175-3d7f3261ca0f · outbound

This paper cites A new quality model for object detection using compressed videos.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning A new quality model for object detection using compressed videos

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.174241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1be07547-2ea0-414d-89c5-5d410aaa9332 · outbound

This paper cites New video enhancement preproces- sor using the region-of-interest for the videoconferencing.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning New video enhancement preproces- sor using the region-of-interest for the videoconferencing

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.162314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d21dee79-066c-4e49-90d0-d745afa2c95b · outbound

This paper cites Most apparent distortion: full-reference image quality assessment and the role of strategy.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Most apparent distortion: full-reference image quality assessment and the role of strategy

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.151117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 746491b1-5e75-422f-beda-7e6d252fd952 · outbound

This paper cites Norm-in- norm loss with faster convergence and better performance for image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Norm-in- norm loss with faster convergence and better performance for image quality assessment

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.140203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d0867b51-21b7-4265-8bf5-befa51c15ba5 · outbound

This paper cites Kadid-10k: A large-scale artificially distorted iqa database.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Kadid-10k: A large-scale artificially distorted iqa database

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.128839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 44229330-792c-49f1-8660-cb847adbf692 · outbound

This paper cites Hallucinated-iqa: No- reference image quality assessment via adversarial learning.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Hallucinated-iqa: No- reference image quality assessment via adversarial learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.116919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 494a5578-9c1c-4265-90e0-480a8cf44ce2 · outbound

This paper cites Visual instruction tuning.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Visual instruction tuning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.426112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b26ccd0e-2601-48eb-be34-f9905f2b044e · outbound

This paper cites Visual instruction tuning.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Visual instruction tuning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.098460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 517aacae-c67c-4c1f-8bf5-dedb156db854 · outbound

This paper cites Rankiqa: Learning from rankings for no-reference image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Rankiqa: Learning from rankings for no-reference image quality assessment

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.086789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 64a8a21e-0ba8-4d18-8325-2f71527ccbdc · outbound

This paper cites A convnet for the 2020s.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning A convnet for the 2020s

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.437170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 786178ff-3937-4fb0-939c-5353b5671a93 · outbound

This paper cites Variable rate roi image compression optimized for visual quality.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Variable rate roi image compression optimized for visual quality

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.068783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e14204fc-e5fe-47d3-8e65-2a9999f1006f · outbound

This paper cites Image quality assessment us- ing contrastive learning.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Image quality assessment us- ing contrastive learning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.444919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7b19100-a4d1-4b09-b22d-da3ad0f9d6df · outbound

This paper cites Vcrnet: Visual compensation restoration network for no-reference image quality assess- ment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Vcrnet: Visual compensation restoration network for no-reference image quality assess- ment

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.049991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 11e9aa05-1234-45f9-b9e3-eb2edc04a520 · outbound

This paper cites Color image database tid2013: Peculiarities and preliminary re- sults.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Color image database tid2013: Peculiarities and preliminary re- sults

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.037381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 48a05332-9256-4be4-83c8-6184c16cdbc7 · outbound

This paper cites Data-efficient image quality assessment with attention-panel decoder.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Data-efficient image quality assessment with attention-panel decoder

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.023911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 85cd7144-ec59-4936-b4a6-7bdd6b7b6fde · outbound

This paper cites A statistical evaluation of recent full reference image quality assessment algorithms.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning A statistical evaluation of recent full reference image quality assessment algorithms

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:44.009992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 252fec46-8a63-4e1e-818a-6728ad5e9ed4 · outbound

This paper cites Transformer-based no-reference image quality assessment via supervised con- trastive learning, 2023.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Transformer-based no-reference image quality assessment via supervised con- trastive learning, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.994181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cb455bd6-2194-4033-9378-91b6eef63861 · outbound

This paper cites Blindly assess image qual- ity in the wild guided by a self-adaptive hyper network.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Blindly assess image qual- ity in the wild guided by a self-adaptive hyper network

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.982106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1cab549b-530e-4453-afe9-dc31b8b9453e · outbound

This paper cites Blind quality assessment for in-the-wild images via hierarchical feature fusion and iterative mixed database training.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Blind quality assessment for in-the-wild images via hierarchical feature fusion and iterative mixed database training

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.470353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa1d2483-6d06-4cc3-897e-d8381d012e8a · outbound

This paper cites Hierarchical curriculum learning for no-reference image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Hierarchical curriculum learning for no-reference image quality assessment

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.962283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1c0465b-cde9-46ed-bdbd-51706f486cdd · outbound

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

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.477524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33520168-dffe-46ee-b077-08c70d43d1d9 · outbound

This paper cites Micro-expression recognition with attention mecha- nism and region enhancement.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Micro-expression recognition with attention mecha- nism and region enhancement

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.949481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bde48490-d234-4583-b435-449313de3719 · outbound

This paper cites Active fine-tuning from gmad examples improves blind image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Active fine-tuning from gmad examples improves blind image quality assessment

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.937139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0629192-d3c4-48e4-9404-4001437f94b8 · outbound

This paper cites Deep blind image quality assessment pow- ered by online hard example mining.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Deep blind image quality assessment pow- ered by online hard example mining

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.925276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a1d94b10-0419-4ca0-a435-0c23be3dc8d8 · outbound

This paper cites Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.492521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27a6c4a0-bede-480d-a1a6-718e8244ca94 · outbound

This paper cites Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.496607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8957b251-661a-40d3-a84c-22d779fee726 · outbound

This paper cites Q-instruct: Improving low-level visual abilities for multi-modality foundation models.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Q-instruct: Improving low-level visual abilities for multi-modality foundation models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.913283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 34459964-e01b-4b3a-b124-417899837206 · outbound

This paper cites Towards open-ended visual qual- ity comparison, 2024.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Towards open-ended visual qual- ity comparison, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.901740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5529f48f-db76-466c-b3f8-15b333482e83 · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.891180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8b77250b-10f8-4d33-8d91-d0d83e0a6de1 · outbound

This paper cites Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.511191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683b01fa-b5ba-4637-ae3f-6026030a3499 · outbound

This paper cites A roi qual- ity adjustable rate control scheme for low bitrate video cod- ing.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning A roi qual- ity adjustable rate control scheme for low bitrate video cod- ing

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.879886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0b9cbc02-ad97-44f5-bb0a-4922d18878e6 · outbound

This paper cites Maniqa: Multi-dimension attention network for no-reference image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.868082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fca55d48-3897-4b97-9bb2-36970c860235 · outbound

This paper cites A roi-based high capacity reversible data hiding scheme with contrast enhancement for medical images.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning A roi-based high capacity reversible data hiding scheme with contrast enhancement for medical images

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.856420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad956542-832b-4237-a75a-bea64f75b6b4 · outbound

This paper cites mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.525709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b47c6fe8-f802-4c46-80b4-97ef1e5a2dfd · outbound

This paper cites From patches to pictures (paq-2-piq): Mapping the perceptual space of pic- ture quality.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning From patches to pictures (paq-2-piq): Mapping the perceptual space of pic- ture quality

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.844682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 14a4456e-1280-4863-adef-235f393bb827 · outbound

This paper cites Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.532916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c89d682-152b-4642-ae65-dcd80184f074 · outbound

This paper cites Descriptive image quality assessment in the wild.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Descriptive image quality assessment in the wild

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.537012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b7bde7f-f783-4de5-bdfa-ffd38fd09411 · outbound

This paper cites Osprey: Pixel understanding with visual instruction tuning, 2024.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Osprey: Pixel understanding with visual instruction tuning, 2024

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.833477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 08298730-5039-441e-93cb-feb7dd0a634f · outbound

This paper cites Blind image quality assessment using a deep bilinear convolutional neural network.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Blind image quality assessment using a deep bilinear convolutional neural network

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.821706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ca9f5d96-50b1-4a4a-9d6a-1d089db21d18 · outbound

This paper cites Blind image quality assessment via vision- language correspondence: A multitask learning perspective.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Blind image quality assessment via vision- language correspondence: A multitask learning perspective

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.810329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2da1ba97-4190-4bd9-a28f-dddb3f1c6655 · outbound

This paper cites Quality-aware pre-trained models for blind image quality assessment.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Quality-aware pre-trained models for blind image quality assessment

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.798225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7b282c9b-018a-468b-93ca-095bb0c4ea03 · outbound

This paper cites Segment everything everywhere all at once.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Segment everything everywhere all at once

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:59:43.786500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 012cf904-f850-4c63-8f79-bdfb9bb97a25 · outbound

This paper cites an unresolved cited work.

SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning Unresolved cited work

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-12T19:59:43.332401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4a662c05-09dd-41e8-b956-9eef91aacce1 · inbound

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment cites this paper.

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.405928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f250c247-cb08-44dc-a9b6-eeedb1f6ef44 · 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 SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:22:43.430265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d85088a-ebe0-4b92-989f-4fd89ae667dd · inbound

ViDA-UGC: Detailed Image Quality Analysis via Visual Distortion Assessment for UGC Images cites this paper.

ViDA-UGC: Detailed Image Quality Analysis via Visual Distortion Assessment for UGC Images SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:52.851606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8c8b3be-d2cc-4ddd-bc6c-a285d744d9cd · inbound

FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution cites this paper.

FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:01:11.709399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.