{"id":"https://openalex.org/W7161551661","doi":"https://doi.org/10.48550/arxiv.2605.15951","title":"From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding","display_name":"From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161551661","doi":"https://doi.org/10.48550/arxiv.2605.15951"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.15951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15951","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.15951","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136448712","display_name":"Yuyuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102637407","display_name":"Yiping Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Yiping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136413157","display_name":"Anjie Le","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le, Anjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136363187","display_name":"Jiayuan Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Jiayuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136441752","display_name":"Jiazhen Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiazhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083735851","display_name":"Can Peng","orcid":"https://orcid.org/0000-0003-1673-2460"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136363283","display_name":"Jiajun Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Jiajun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113214813","display_name":"F. Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Fengbei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136429500","display_name":"Junde Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Junde","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9460999965667725,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9460999965667725,"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/T10028","display_name":"Topic Modeling","score":0.012299999594688416,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12031","display_name":"Speech and dialogue systems","score":0.007499999832361937,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6509000062942505},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5357000231742859},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5084999799728394},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.39250001311302185},{"id":"https://openalex.org/keywords/ground","display_name":"Ground","score":0.3538999855518341},{"id":"https://openalex.org/keywords/consolidation","display_name":"Consolidation (business)","score":0.34119999408721924}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6509000062942505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6308000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6171000003814697},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5357000231742859},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5084999799728394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4595000147819519},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.39250001311302185},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.15951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15951","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.15951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15951","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"Finetuning":[0],"Large":[1],"Vision-Language":[2],"Models":[3],"with":[4,68,144],"reinforcement":[5],"learning":[6,41,62],"has":[7],"emerged":[8],"as":[9],"a":[10,56,69,75,91],"promising":[11],"approach":[12],"to":[13,39,80,114],"enhance":[14],"their":[15],"capability":[16],"in":[17,48],"object-level":[18],"grounding.":[19],"However,":[20],"existing":[21],"methods,":[22],"mainly":[23],"based":[24],"on":[25,63],"GRPO,":[26],"assign":[27],"rewards":[28],"at":[29,152],"the":[30,100,117,121,124],"response":[31,72],"level.":[32],"Such":[33],"sparse":[34],"reward,":[35],"often":[36],"criterion-induced,":[37],"leads":[38],"minimal":[40],"signals":[42,111],"when":[43],"all":[44],"candidate":[45],"responses":[46],"fail":[47],"challenging":[49],"scenarios.":[50],"In":[51],"this":[52],"work,":[53],"we":[54,89],"propose":[55],"group-revision":[57],"optimisation":[58],"paradigm":[59],"that":[60,94],"enhances":[61],"hard":[64],"cases.":[65],"It":[66],"begins":[67],"sampled":[70],"initial":[71,101],"and":[73,103,119,136,140],"generates":[74],"set":[76],"of":[77,126],"revised":[78],"candidates":[79],"explore":[81],"improved":[82],"grounding":[83],"outcomes.":[84],"Inspired":[85],"by":[86],"reward":[87,118],"shaping,":[88],"introduce":[90],"consolidation":[92],"process":[93],"quantifies":[95],"each":[96],"candidate's":[97],"improvement":[98],"over":[99],"attempt":[102],"converts":[104],"it":[105],"into":[106],"informative":[107],"shaping":[108],"signals.":[109],"These":[110],"are":[112],"used":[113],"both":[115],"refine":[116],"modulate":[120],"advantage,":[122],"amplifying":[123],"influence":[125],"high-quality":[127],"revisions.":[128],"Our":[129,148],"method":[130],"achieves":[131],"consistent":[132],"gains":[133],"across":[134],"referring":[135],"reasoning":[137],"segmentation,":[138],"REC,":[139],"counting":[141],"benchmarks":[142],"compared":[143],"prior":[145],"GRPO-based":[146],"models.":[147],"code":[149],"is":[150],"available":[151],"https://github.com/yyliu01/GroupRevision.":[153]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-19T00:00:00"}
