{"id":"https://openalex.org/W7127364683","doi":"https://doi.org/10.48550/arxiv.2602.01611","title":"What Do Agents Learn from Trajectory-SFT: Semantics or Interfaces?","display_name":"What Do Agents Learn from Trajectory-SFT: Semantics or Interfaces?","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127364683","doi":"https://doi.org/10.48550/arxiv.2602.01611"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.01611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051103878","display_name":"Weili Gu","orcid":"https://orcid.org/0000-0002-0448-110X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gu, Weizheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124952516","display_name":"Chengze Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chengze","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010912592","display_name":"Zhuohao Yu","orcid":"https://orcid.org/0009-0006-0037-0396"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Zhuohao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038482830","display_name":"Mingze Sun","orcid":"https://orcid.org/0000-0003-0027-0003"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Mengyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124872810","display_name":"Zhibang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhibang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124896764","display_name":"Wei J. Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124920853","display_name":"Hongrui Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Hongrui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124897517","display_name":"Shikun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shikun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124954806","display_name":"Wei Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Wei","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5051103878"],"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.15770000219345093,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.15770000219345093,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.13819999992847443,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.06599999964237213,"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/interface","display_name":"Interface (matter)","score":0.809499979019165},{"id":"https://openalex.org/keywords/conflation","display_name":"Conflation","score":0.7156000137329102},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6507999897003174},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6437000036239624},{"id":"https://openalex.org/keywords/rewriting","display_name":"Rewriting","score":0.5109000205993652},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5094000101089478},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.45680001378059387}],"concepts":[{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.809499979019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789900004863739},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.7156000137329102},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6507999897003174},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6437000036239624},{"id":"https://openalex.org/C154690210","wikidata":"https://www.wikidata.org/wiki/Q1668499","display_name":"Rewriting","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5094000101089478},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.48240000009536743},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.46470001339912415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4641999900341034},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45680001378059387},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38260000944137573},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3292999863624573},{"id":"https://openalex.org/C174252522","wikidata":"https://www.wikidata.org/wiki/Q3816772","display_name":"Natural language user interface","level":3,"score":0.32760000228881836},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.250900000333786},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.01611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},{"id":"doi:10.48550/arxiv.2602.01611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.01611","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.01611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"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":{"Large":[0],"language":[1],"models":[2,105],"are":[3,42],"increasingly":[4],"evaluated":[5],"as":[6],"interactive":[7],"agents,":[8,86],"yet":[9],"standard":[10,139],"agent":[11],"benchmarks":[12],"conflate":[13],"two":[14],"qualitatively":[15],"distinct":[16],"sources":[17],"of":[18,46,82],"success:":[19],"semantic":[20],"tool-use":[21],"and":[22,69,77,79,84,125],"interface-specific":[23],"interaction":[24],"pattern":[25],"memorization.":[26],"Because":[27],"both":[28],"mechanisms":[29],"can":[30],"yield":[31],"identical":[32],"task":[33,67],"success":[34],"on":[35],"the":[36],"original":[37],"interface,":[38],"benchmark":[39],"scores":[40],"alone":[41],"not":[43],"identifiable":[44],"evidence":[45],"environment-invariant":[47],"capability.":[48],"We":[49,109],"propose":[50],"PIPE,":[51],"a":[52,80,115],"protocol-level":[53],"evaluation":[54],"augmentation":[55],"for":[56,122],"diagnosing":[57],"interface":[58,93,101,128],"reliance":[59],"by":[60],"minimally":[61],"rewriting":[62],"environment":[63],"interfaces":[64],"while":[65,103],"preserving":[66],"semantics":[68],"execution":[70],"behavior.":[71],"Across":[72],"16":[73],"environments":[74],"from":[75],"AgentBench":[76],"AgentGym":[78],"range":[81],"open-source":[83],"API-based":[85],"PIPE":[87],"reveals":[88],"that":[89,119,127,135],"trajectory-SFT":[90],"substantially":[91],"amplifies":[92],"shortcutting:":[94],"trained":[95],"agents":[96],"degrade":[97],"sharply":[98],"under":[99,138],"minimal":[100],"rewrites,":[102],"non-trajectory-trained":[104],"remain":[106,136],"largely":[107],"stable.":[108],"further":[110],"introduce":[111],"Interface":[112],"Reliance":[113],"(IR),":[114],"counterbalanced":[116],"alias-based":[117],"metric":[118],"quantifies":[120],"preference":[121],"training-time":[123],"interfaces,":[124],"show":[126],"shortcutting":[129],"exhibits":[130],"environment-dependent,":[131],"non-monotonic":[132],"training":[133],"dynamics":[134],"invisible":[137],"evaluation.":[140],"Our":[141],"code":[142],"is":[143],"available":[144],"at":[145],"https://anonymous.4open.science/r/What-Do-Agents-Learn-from-Trajectory-SFT-Semantics-or-Interfaces--0831/.":[146]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-04T00:00:00"}
