{"id":"https://openalex.org/W7159641083","doi":"https://doi.org/10.48550/arxiv.2604.28078","title":"AesRM: Improving Video Aesthetics with Expert-Level Feedback","display_name":"AesRM: Improving Video Aesthetics with Expert-Level Feedback","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159641083","doi":"https://doi.org/10.48550/arxiv.2604.28078"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.28078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28078","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.28078","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134961721","display_name":"Yujin Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Yujin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134972089","display_name":"Yujie Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Yujie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134938606","display_name":"Yefei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Yefei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134946628","display_name":"Xinyu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134968494","display_name":"Tianle Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianle","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112840113","display_name":"Zichao Yu","orcid":"https://orcid.org/0009-0005-8880-279X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Zichao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031625303","display_name":"Andi Han","orcid":"https://orcid.org/0000-0003-4655-655X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Andi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134935044","display_name":"Shiwei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shiwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134933105","display_name":"Tingyu Weng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weng, Tingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134962421","display_name":"Difan Zou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zou, Difan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.005499999970197678,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.003700000001117587,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.45190000534057617},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4138000011444092},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.37630000710487366},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.352400004863739},{"id":"https://openalex.org/keywords/filmmaking","display_name":"Filmmaking","score":0.310699999332428},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3073999881744385},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.30140000581741333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6686000227928162},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.45190000534057617},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.3968999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3912000060081482},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3625999987125397},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C68389820","wikidata":"https://www.wikidata.org/wiki/Q932586","display_name":"Filmmaking","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3073999881744385},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C111640148","wikidata":"https://www.wikidata.org/wiki/Q847349","display_name":"Rubric","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.27619999647140503},{"id":"https://openalex.org/C543847140","wikidata":"https://www.wikidata.org/wiki/Q2642826","display_name":"Realism","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C2780310081","wikidata":"https://www.wikidata.org/wiki/Q1154312","display_name":"Video editing","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.28078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28078","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.28078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28078","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"rapid":[1],"advances":[2],"in":[3],"photorealistic":[4],"video":[5,13,50,59,98],"generation,":[6],"real-world":[7],"applications":[8],"such":[9],"as":[10],"filmmaking":[11],"require":[12],"aesthetics,":[14,51],"e.g.,":[15,39,79,170],"harmonious":[16],"colors":[17],"and":[18,45,71,90,106,133,184,204,221,235],"cinematic":[19],"lighting,":[20],"beyond":[21],"visual":[22,27,40],"fidelity.":[23],"Prior":[24],"work":[25],"on":[26,31,103,125,217],"aesthetics":[28,35,60,219],"largely":[29],"focuses":[30],"images,":[32],"often":[33],"reducing":[34],"to":[36,128,144,200],"coarse":[37],"definitions,":[38],"pleasure,":[41],"without":[42],"a":[43,54,85,111,153],"rigorous":[44],"systematic":[46],"evaluation.":[47],"To":[48,191],"improve":[49,145,201],"we":[52,149,194,230],"propose":[53,196],"hierarchical":[55],"rubric":[56],"that":[57],"decomposes":[58],"into":[61],"three":[62],"core":[63],"dimensions,":[64],"Visual":[65,68,72],"Aesthetics":[66],"(VA),":[67],"Fidelity":[69],"(VF),":[70],"Plausibility":[73],"(VP),":[74],"with":[75,100,140,152,180,225,233],"15":[76,142],"fine-grained":[77],"criteria,":[78],"shot":[80],"composition.":[81],"This":[82],"framework":[83],"enables":[84],"large-scale":[86],"expert-annotated":[87],"preference":[88],"dataset":[89],"an":[91],"evaluation":[92,189],"benchmark,":[93],"AesVideo-Bench,":[94],"containing":[95],"about":[96],"2500":[97],"pairs":[99],"expert":[101],"annotations":[102],"VA,":[104],"VF,":[105],"VP.":[107],"We":[108],"then":[109],"build":[110],"family":[112],"of":[113,166],"Video":[114],"Aesthetic":[115,159],"Reward":[116],"Models":[117],"(AesRM):":[118],"AesRM-Base,":[119],"which":[120,135,162],"directly":[121],"predicts":[122],"pairwise":[123],"preferences":[124],"these":[126],"dimensions":[127],"provide":[129],"efficient":[130],"post-training":[131],"rewards,":[132],"AesRM-CoT,":[134,193],"additionally":[136,195],"generates":[137],"CoT":[138,198,202],"aligned":[139],"all":[141],"criteria":[143],"assessment":[146],"interpretability.":[147],"Specifically,":[148],"train":[150],"AesRM":[151,214,234],"three-stage":[154],"progressive":[155],"scheme:":[156],"(1)":[157],"Atomic":[158],"Capability":[160],"Learning,":[161],"strengthens":[163],"AesRM's":[164],"recognition":[165],"fundamental":[167],"aesthetic":[168,238,242],"concepts,":[169],"accurately":[171],"identifying":[172],"centered":[173],"composition;":[174],"(2)":[175],"Cold-Start,":[176],"aligning":[177],"the":[178],"model":[179],"structured":[181],"reasoning":[182],"protocols;":[183],"(3)":[185],"GRPO,":[186],"further":[187],"improving":[188],"accuracy.":[190],"enhance":[192],"self-consistency-based":[197],"synthesis":[199],"quality":[203],"design":[205],"CoT-based":[206],"process":[207],"rewards":[208],"during":[209],"GRPO.":[210],"Extensive":[211],"experiments":[212],"show":[213],"outperforms":[215],"baselines":[216],"multiple":[218],"benchmarks":[220],"is":[222],"more":[223],"robust,":[224],"lower":[226],"position":[227],"bias.":[228],"Finally,":[229],"align":[231],"Wan2.2":[232],"observe":[236],"clear":[237],"gains":[239],"over":[240],"existing":[241],"reward":[243],"models.":[244]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-02T00:00:00"}