{"id":"https://openalex.org/W4388787672","doi":"https://doi.org/10.48550/arxiv.2311.09528","title":"HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM","display_name":"HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM","publication_year":2023,"publication_date":"2023-11-16","ids":{"openalex":"https://openalex.org/W4388787672","doi":"https://doi.org/10.48550/arxiv.2311.09528"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.09528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.09528","pdf_url":"https://arxiv.org/pdf/2311.09528","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.09528","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101475389","display_name":"Zhilin Wang","orcid":"https://orcid.org/0000-0002-0188-0332"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100650289","display_name":"Yi Dong","orcid":"https://orcid.org/0000-0003-3047-7777"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055726090","display_name":"Jiaqi Zeng","orcid":"https://orcid.org/0000-0002-6967-5394"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112105145","display_name":"Virginia Adams","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adams, Virginia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111090196","display_name":"Makesh Narsimhan Sreedhar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sreedhar, Makesh Narsimhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093285949","display_name":"Daniel Egert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Egert, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065423636","display_name":"Olivier Delalleau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Delalleau, Olivier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093285950","display_name":"Jane Polak Scowcroft","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Scowcroft, Jane Polak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044949020","display_name":"Neel Kant","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kant, Neel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012493437","display_name":"Aidan Swope","orcid":"https://orcid.org/0009-0006-4685-8709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swope, Aidan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048403564","display_name":"Oleksii Kuchaiev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuchaiev, Oleksii","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":1,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.963100016117096,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.963100016117096,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9603999853134155,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9362000226974487,"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/helpfulness","display_name":"Helpfulness","score":0.9900486469268799},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.760762631893158},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.6484676599502563},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4945840537548065},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44716984033584595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4060068130493164},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38084396719932556},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10405024886131287},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09055119752883911}],"concepts":[{"id":"https://openalex.org/C2781265381","wikidata":"https://www.wikidata.org/wiki/Q5710255","display_name":"Helpfulness","level":2,"score":0.9900486469268799},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.760762631893158},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6484676599502563},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4945840537548065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44716984033584595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4060068130493164},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38084396719932556},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10405024886131287},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09055119752883911},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2311.09528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.09528","pdf_url":"https://arxiv.org/pdf/2311.09528","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.09528","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.09528","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":"pmh:oai:arXiv.org:2311.09528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.09528","pdf_url":"https://arxiv.org/pdf/2311.09528","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2613921548","https://openalex.org/W4285360723","https://openalex.org/W4281847990","https://openalex.org/W2488228222","https://openalex.org/W3037056935","https://openalex.org/W2002563848","https://openalex.org/W2934621214","https://openalex.org/W1498449133","https://openalex.org/W2611407113","https://openalex.org/W2092282862"],"abstract_inverted_index":{"Existing":[0],"open-source":[1],"helpfulness":[2,50,77],"preference":[3],"datasets":[4,22],"do":[5,110],"not":[6,111],"specify":[7],"what":[8],"makes":[9],"some":[10],"responses":[11,35,59],"more":[12,116],"helpful":[13],"and":[14,71],"others":[15],"less":[16],"so.":[17],"Models":[18],"trained":[19],"on":[20,97],"these":[21],"can":[23],"incidentally":[24],"learn":[25],"to":[26,38,75],"model":[27,93],"dataset":[28,51,64,87,124],"artifacts":[29],"(e.g.":[30,119],"preferring":[31],"longer":[32],"but":[33],"unhelpful":[34],"only":[36],"due":[37],"their":[39],"length).":[40],"To":[41],"alleviate":[42],"this":[43,123],"problem,":[44],"we":[45],"collect":[46],"HelpSteer,":[47],"a":[48,92],"multi-attribute":[49],"annotated":[52],"for":[53,67,106],"the":[54,85,103],"various":[55],"aspects":[56],"that":[57,94,109],"make":[58],"helpful.":[60],"Specifically,":[61],"our":[62],"37k-sample":[63],"has":[65],"annotations":[66],"correctness,":[68],"coherence,":[69],"complexity,":[70],"verbosity":[72],"in":[73],"addition":[74],"overall":[76],"of":[78],"responses.":[79],"Training":[80],"Llama":[81],"2":[82],"70B":[83],"using":[84],"HelpSteer":[86],"with":[88,125],"SteerLM":[89],"technique":[90],"produces":[91],"scores":[95],"7.54":[96],"MT":[98],"Bench,":[99],"which":[100],"is":[101],"currently":[102],"highest":[104],"score":[105],"open":[107],"models":[108,118],"require":[112],"training":[113],"data":[114],"from":[115],"powerful":[117],"GPT4).":[120],"We":[121],"release":[122],"CC-BY-4.0":[126],"license":[127],"at":[128],"https://huggingface.co/datasets/nvidia/HelpSteer":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}