{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ETGINXVMZ7YPA7RNOZ7E3VGXBV","short_pith_number":"pith:ETGINXVM","schema_version":"1.0","canonical_sha256":"24cc86deaccff0f07e2d767e4dd4d70d7940aa7ef774f1f8e401e686a540e0d9","source":{"kind":"arxiv","id":"2502.14908","version":2},"attestation_state":"computed","paper":{"title":"SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Abhinand Jha, Kathleen M. Carley, Nikitha Rao, Peter Carragher, R Raghav","submitted_at":"2025-02-19T00:26:38Z","abstract_excerpt":"Vision language models (VLM) demonstrate sophisticated multimodal reasoning yet are prone to hallucination when confronted with knowledge conflicts, impeding their deployment in information-sensitive contexts. While existing research addresses robustness in unimodal models, the multimodal domain lacks systematic investigation of cross-modal knowledge conflicts. This research introduces \\segsub, a framework for applying targeted image perturbations to investigate VLM resilience against knowledge conflicts. Our analysis reveals distinct vulnerability patterns: while VLMs are robust to parametric"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2502.14908","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-19T00:26:38Z","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"title_canon_sha256":"e7981901fc9d8958b4af1359e1d403c44bd450fdb79ca4e40e81919958bd272c","abstract_canon_sha256":"3a321ecf14de4ece849d0f3a2a626b4f9ff1ab86ebe5ad66fc37cb43099a62b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:27.188160Z","signature_b64":"CPvjdtOhzS/R3SIKBP4+clR5sq7FlNIazEMFN/hKhaihIdUxaTvs4zG5TgHyVCDQAgBZNCK4HrY+ji4PC/DGDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24cc86deaccff0f07e2d767e4dd4d70d7940aa7ef774f1f8e401e686a540e0d9","last_reissued_at":"2026-07-05T11:38:27.187599Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:27.187599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Abhinand Jha, Kathleen M. Carley, Nikitha Rao, Peter Carragher, R Raghav","submitted_at":"2025-02-19T00:26:38Z","abstract_excerpt":"Vision language models (VLM) demonstrate sophisticated multimodal reasoning yet are prone to hallucination when confronted with knowledge conflicts, impeding their deployment in information-sensitive contexts. While existing research addresses robustness in unimodal models, the multimodal domain lacks systematic investigation of cross-modal knowledge conflicts. This research introduces \\segsub, a framework for applying targeted image perturbations to investigate VLM resilience against knowledge conflicts. Our analysis reveals distinct vulnerability patterns: while VLMs are robust to parametric"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.14908","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2502.14908/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2502.14908","created_at":"2026-07-05T11:38:27.187681+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.14908v2","created_at":"2026-07-05T11:38:27.187681+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.14908","created_at":"2026-07-05T11:38:27.187681+00:00"},{"alias_kind":"pith_short_12","alias_value":"ETGINXVMZ7YP","created_at":"2026-07-05T11:38:27.187681+00:00"},{"alias_kind":"pith_short_16","alias_value":"ETGINXVMZ7YPA7RN","created_at":"2026-07-05T11:38:27.187681+00:00"},{"alias_kind":"pith_short_8","alias_value":"ETGINXVM","created_at":"2026-07-05T11:38:27.187681+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV","json":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV.json","graph_json":"https://pith.science/api/pith-number/ETGINXVMZ7YPA7RNOZ7E3VGXBV/graph.json","events_json":"https://pith.science/api/pith-number/ETGINXVMZ7YPA7RNOZ7E3VGXBV/events.json","paper":"https://pith.science/paper/ETGINXVM"},"agent_actions":{"view_html":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV","download_json":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV.json","view_paper":"https://pith.science/paper/ETGINXVM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.14908&json=true","fetch_graph":"https://pith.science/api/pith-number/ETGINXVMZ7YPA7RNOZ7E3VGXBV/graph.json","fetch_events":"https://pith.science/api/pith-number/ETGINXVMZ7YPA7RNOZ7E3VGXBV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV/action/storage_attestation","attest_author":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV/action/author_attestation","sign_citation":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV/action/citation_signature","submit_replication":"https://pith.science/pith/ETGINXVMZ7YPA7RNOZ7E3VGXBV/action/replication_record"}},"created_at":"2026-07-05T11:38:27.187681+00:00","updated_at":"2026-07-05T11:38:27.187681+00:00"}