{"id":"https://openalex.org/W7204271256","doi":"https://doi.org/10.48550/arxiv.2608.24667","title":"EviGraph: Towards Verifiable Evidence Construction for Information-Seeking Agents","display_name":"EviGraph: Towards Verifiable Evidence Construction for Information-Seeking Agents","publication_year":2026,"publication_date":"2026-08-25","ids":{"openalex":"https://openalex.org/W7204271256","doi":"https://doi.org/10.48550/arxiv.2608.24667"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.24667","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24667","pdf_url":"https://arxiv.org/pdf/2608.24667","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,"listed_in":[],"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"parent_works":[],"lineage":["https://openalex.org/W7204271256"],"child_works_count":0,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.24667","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102853909","display_name":"Jiashun Chen","orcid":"https://orcid.org/0000-0003-0254-4303","observed_orcids":["https://orcid.org/0000-0003-0254-4303"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Jiashun","raw_affiliation_strings":["Tencent Inc. , Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Inc. , Beijing , China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070280999","display_name":"Yirong Mao","orcid":"https://orcid.org/0000-0002-7603-4341","observed_orcids":["https://orcid.org/0000-0002-7603-4341"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mao, Yirong","raw_affiliation_strings":["Tencent Inc. , Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Inc. , Beijing , China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053614230","display_name":"Wenhui Que","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Que, Wenhui","raw_affiliation_strings":["Tencent Inc. , Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Inc. , Beijing , China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9794999957084656,"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"}},"topics":[{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9794999957084656,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.006500000134110451,"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":0.004800000227987766,"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/evidence-construction","display_name":"evidence construction","score":0.781000018119812},{"id":"https://openalex.org/keywords/evidence-verification","display_name":"evidence verification","score":0.6159999966621399},{"id":"https://openalex.org/keywords/grounded-language-models","display_name":"grounded language models","score":0.45100000500679016},{"id":"https://openalex.org/keywords/query-planning","display_name":"query planning","score":0.4950000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.803600013256073},{"id":"https://openalex.org/C180591056","wikidata":"https://www.wikidata.org/wiki/Q654437","display_name":"Executor","level":2,"score":0.7520999908447266},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7153000235557556},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5799000263214111},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.5342000126838684},{"id":"https://openalex.org/C2775945657","wikidata":"https://www.wikidata.org/wiki/Q381442","display_name":"Structuring","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.483599990606308},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.461899995803833},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3294999897480011},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3278999924659729},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26159998774528503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.259799987077713}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.24667","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24667","pdf_url":"https://arxiv.org/pdf/2608.24667","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,"listed_in":[],"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.24667","doi":"https://doi.org/10.48550/arxiv.2608.24667","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.24667","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,"listed_in":[],"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.24667","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24667","pdf_url":"https://arxiv.org/pdf/2608.24667","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,"listed_in":[],"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204271256.pdf","grobid_xml":"https://content.openalex.org/works/W7204271256.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W2889787757","https://openalex.org/W2950336186","https://openalex.org/W4387636003","https://openalex.org/W4388964563","https://openalex.org/W4389519598","https://openalex.org/W4389520670","https://openalex.org/W4391631327","https://openalex.org/W4407759090","https://openalex.org/W4412877046","https://openalex.org/W4414939355","https://openalex.org/W4414990013","https://openalex.org/W4415109242","https://openalex.org/W4415194584","https://openalex.org/W4415947132","https://openalex.org/W4416034676","https://openalex.org/W4416035997","https://openalex.org/W4416048747","https://openalex.org/W4416256501","https://openalex.org/W4416384298","https://openalex.org/W4416526576","https://openalex.org/W4416679470","https://openalex.org/W4416780398","https://openalex.org/W4416895257","https://openalex.org/W4417089504","https://openalex.org/W4417092508","https://openalex.org/W4417252869","https://openalex.org/W4417422257","https://openalex.org/W4417459294","https://openalex.org/W6891936057","https://openalex.org/W6948369276","https://openalex.org/W7080402243","https://openalex.org/W7126150514","https://openalex.org/W7140209607","https://openalex.org/W7160533687","https://openalex.org/W7164192805","https://openalex.org/W7166830541"],"related_works":["https://openalex.org/W7162084384","https://openalex.org/W7212239874","https://openalex.org/W7171516988","https://openalex.org/W7161583407","https://openalex.org/W7221762665","https://openalex.org/W7162685862","https://openalex.org/W7201861027","https://openalex.org/W7214898040","https://openalex.org/W7167931267","https://openalex.org/W7202180134"],"abstract_inverted_index":{"Agentic":[0],"Web":[1],"search":[2,25,54,192],"can":[3],"retrieve":[4],"relevant":[5],"information":[6],"without":[7,160],"establishing":[8],"that":[9,52,99,183],"the":[10,15,65,90,135,156],"retrieved":[11],"content":[12],"actually":[13],"supports":[14],"claims":[16],"used":[17],"in":[18,29],"an":[19,86],"answer.":[20,137],"Existing":[21],"agents":[22],"typically":[23],"keep":[24],"and":[26,34,80,89,116,163,180,186],"evidence":[27,57,75,83,130,188],"recording":[28,58,189],"a":[30,49,61,73,103,118,140,148,166],"linear":[31],"interaction":[32,150],"trace":[33],"optimize":[35],"primarily":[36],"for":[37,43,64,155,165],"final-answer":[38],"correctness,":[39],"providing":[40],"limited":[41],"supervision":[42],"intermediate":[44],"grounding.":[45],"We":[46],"present":[47],"EviGraph,":[48],"deep-search":[50],"framework":[51],"separates":[53],"execution":[55],"from":[56],"while":[59,169],"using":[60],"shared":[62],"policy":[63,91],"trainable":[66],"roles.":[67],"An":[68],"executor":[69],"plans":[70],"concise":[71],"queries,":[72],"frozen":[74],"verifier":[76],"inspects":[77],"source":[78,119],"pages":[79],"returns":[81],"verbatim":[82],"items":[84,94],"with":[85,153],"explicit":[87],"polarity,":[88],"maps":[92],"those":[93],"to":[95,127],"add/support":[96],"graph":[97,109],"requests":[98],"are":[100],"checked":[101],"by":[102],"deterministic":[104],"structural":[105],"validator.":[106],"The":[107],"resulting":[108],"serves":[110],"both":[111],"as":[112,117],"persistent":[113],"working":[114],"memory":[115],"of":[120],"dense":[121],"process":[122],"rewards,":[123],"enabling":[124],"reinforcement":[125,161],"learning":[126,162],"directly":[128],"supervise":[129],"construction":[131],"rather":[132],"than":[133],"only":[134],"final":[136],"On":[138],"BrowseComp-Plus,":[139],"Qwen3-8B":[141],"EviGraph":[142],"agent":[143],"achieves":[144],"35.9%":[145],"accuracy":[146],"under":[147],"matched":[149],"budget,":[151],"compared":[152],"26.9%":[154],"same":[157],"dual-role":[158],"architecture":[159],"2.7%":[164],"monolithic":[167],"agent,":[168],"generating":[170],"fewer":[171],"tokens":[172],"per":[173],"rollout.":[174],"Consistent":[175],"gains":[176],"on":[177],"BrowseComp,":[178],"GAIA,":[179],"XBench":[181],"indicate":[182],"explicitly":[184],"structuring":[185],"rewarding":[187],"improves":[190],"agentic":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2026-08-27T00:00:00"}