{"id":"https://openalex.org/W7125939460","doi":"https://doi.org/10.48550/arxiv.2601.19120","title":"RobustExplain: Evaluating Robustness of LLM-Based Explanation Agents for Recommendation","display_name":"RobustExplain: Evaluating Robustness of LLM-Based Explanation Agents for Recommendation","publication_year":2026,"publication_date":"2026-01-27","ids":{"openalex":"https://openalex.org/W7125939460","doi":"https://doi.org/10.48550/arxiv.2601.19120"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.19120","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/A5121269801","display_name":"Guilin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Guilin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124100951","display_name":"Kai Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Kai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124055871","display_name":"Jeffrey Friedman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Friedman, Jeffrey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124073057","display_name":"Xu Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Xu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5121269801"],"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8471999764442444,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8471999764442444,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.02930000051856041,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.021199999377131462,"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/robustness","display_name":"Robustness (evolution)","score":0.883400022983551},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5012999773025513},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.3059000074863434},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.2939000129699707},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.2937999963760376}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.883400022983551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207000255584717},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5029000043869019},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5012999773025513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4334000051021576},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32710000872612},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C118643609","wikidata":"https://www.wikidata.org/wiki/Q189210","display_name":"Web application","level":2,"score":0.24719999730587006}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.19120","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.2601.19120","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.19120","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.2601.19120","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":[{"score":0.696441113948822,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"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],"(LLMs)":[3],"are":[4,56],"increasingly":[5],"used":[6],"to":[7,42,60,121,134,162],"generate":[8],"natural-language":[9],"explanations":[10,41],"in":[11],"recommender":[12,186],"systems,":[13],"acting":[14],"as":[15,179],"explanation":[16,30,73,174],"agents":[17,175],"that":[18,150],"reason":[19],"over":[20],"user":[21,44,76,98],"behavior":[22,45,99],"histories.":[23],"While":[24],"prior":[25],"work":[26],"has":[27],"focused":[28],"on":[29,144],"fluency":[31],"and":[32,67,75,106,115,128,176],"relevance":[33],"under":[34],"fixed":[35],"inputs,":[36],"the":[37,81,88,169],"robustness":[38,89,109,130,171,178],"of":[39,90],"LLM-generated":[40,91],"realistic":[43,97],"noise":[46],"remains":[47],"largely":[48],"unexplored.":[49],"In":[50],"real-world":[51],"web":[52,189],"platforms,":[53],"interaction":[54],"histories":[55],"inherently":[57],"noisy":[58],"due":[59],"accidental":[61],"clicks,":[62],"temporal":[63],"inconsistencies,":[64],"missing":[65],"values,":[66],"evolving":[68],"preferences,":[69],"raising":[70],"concerns":[71],"about":[72],"stability":[74],"trust.":[77],"We":[78],"present":[79],"RobustExplain,":[80],"first":[82,170],"systematic":[83],"evaluation":[84,126],"framework":[85,127],"for":[86,173,183],"measuring":[87],"recommendation":[92],"explanations.":[93],"RobustExplain":[94],"introduces":[95],"five":[96],"perturbations":[100],"evaluated":[101],"across":[102,139],"multiple":[103],"severity":[104],"levels":[105],"a":[107,123,136,180],"multi-dimensional":[108],"metric":[110],"capturing":[111],"semantic,":[112],"keyword,":[113],"structural,":[114],"length":[116],"consistency.":[117],"Our":[118,166],"goal":[119],"is":[120],"establish":[122,168],"principled,":[124],"task-level":[125],"initial":[129],"baselines,":[131],"rather":[132],"than":[133],"provide":[135],"comprehensive":[137],"leaderboard":[138],"all":[140],"available":[141],"LLMs.":[142],"Experiments":[143],"four":[145],"representative":[146],"LLMs":[147],"(7B--70B)":[148],"show":[149],"current":[151],"models":[152,159],"exhibit":[153],"only":[154],"moderate":[155],"robustness,":[156],"with":[157],"larger":[158],"achieving":[160],"up":[161],"8%":[163],"higher":[164],"stability.":[165],"results":[167],"benchmarks":[172],"highlight":[177],"critical":[181],"dimension":[182],"trustworthy,":[184],"agent-driven":[185],"systems":[187],"at":[188],"scale.":[190]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-01-29T00:00:00"}