{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:QZH6HXQC7JDLGOMTEVA4XPO3PT","short_pith_number":"pith:QZH6HXQC","schema_version":"1.0","canonical_sha256":"864fe3de02fa46b339932541cbbddb7cf87d73703aec47e775617e980ca63fa8","source":{"kind":"arxiv","id":"2606.18262","version":1},"attestation_state":"computed","paper":{"title":"When Prompts Mislead: Textual Dominance and Diagnostic Bias in MLLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Doohyun Park, Inhyuk Park","submitted_at":"2026-05-11T08:59:49Z","abstract_excerpt":"Multimodal large language models (MLLMs) are increasingly being evaluated for medical applications, where computational constraints often make prompting strategies the only practical alternative to fine-tuning. Such strategies are generally assumed to support diagnostic reasoning, yet their potential failure modes in medical MLLMs remain poorly characterized. We analyze FundusExpert-1B, an open-source ophthalmology MLLM, on a hemorrhage versus drusen discrimination task using the public BRSET dataset, adopted here as a controlled testbed for our analysis. (i) A controlled probe with artificial"},"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":"2606.18262","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-11T08:59:49Z","cross_cats_sorted":[],"title_canon_sha256":"c398ff52d65d87a915beba950d29a7dcddc80c89bd883003327ef568580952c4","abstract_canon_sha256":"0c56c1ae51477ed4d7ef15f0180f5a289605f4b0a915024491c0cec276b9a309"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:10:56.425868Z","signature_b64":"MKSWESpVemxxU56Wi/MnH7BwPSV2KCOqeHG4NBIpg1eZkLNoXLfGkxIDg//b6iAZfmhFT1sh9xphr0QlLAhlDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"864fe3de02fa46b339932541cbbddb7cf87d73703aec47e775617e980ca63fa8","last_reissued_at":"2026-06-19T16:10:56.425512Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:10:56.425512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"When Prompts Mislead: Textual Dominance and Diagnostic Bias in MLLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Doohyun Park, Inhyuk Park","submitted_at":"2026-05-11T08:59:49Z","abstract_excerpt":"Multimodal large language models (MLLMs) are increasingly being evaluated for medical applications, where computational constraints often make prompting strategies the only practical alternative to fine-tuning. Such strategies are generally assumed to support diagnostic reasoning, yet their potential failure modes in medical MLLMs remain poorly characterized. We analyze FundusExpert-1B, an open-source ophthalmology MLLM, on a hemorrhage versus drusen discrimination task using the public BRSET dataset, adopted here as a controlled testbed for our analysis. (i) A controlled probe with artificial"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18262","kind":"arxiv","version":1},"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/2606.18262/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":"2606.18262","created_at":"2026-06-19T16:10:56.425570+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.18262v1","created_at":"2026-06-19T16:10:56.425570+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18262","created_at":"2026-06-19T16:10:56.425570+00:00"},{"alias_kind":"pith_short_12","alias_value":"QZH6HXQC7JDL","created_at":"2026-06-19T16:10:56.425570+00:00"},{"alias_kind":"pith_short_16","alias_value":"QZH6HXQC7JDLGOMT","created_at":"2026-06-19T16:10:56.425570+00:00"},{"alias_kind":"pith_short_8","alias_value":"QZH6HXQC","created_at":"2026-06-19T16:10:56.425570+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/QZH6HXQC7JDLGOMTEVA4XPO3PT","json":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT.json","graph_json":"https://pith.science/api/pith-number/QZH6HXQC7JDLGOMTEVA4XPO3PT/graph.json","events_json":"https://pith.science/api/pith-number/QZH6HXQC7JDLGOMTEVA4XPO3PT/events.json","paper":"https://pith.science/paper/QZH6HXQC"},"agent_actions":{"view_html":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT","download_json":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT.json","view_paper":"https://pith.science/paper/QZH6HXQC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.18262&json=true","fetch_graph":"https://pith.science/api/pith-number/QZH6HXQC7JDLGOMTEVA4XPO3PT/graph.json","fetch_events":"https://pith.science/api/pith-number/QZH6HXQC7JDLGOMTEVA4XPO3PT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT/action/storage_attestation","attest_author":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT/action/author_attestation","sign_citation":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT/action/citation_signature","submit_replication":"https://pith.science/pith/QZH6HXQC7JDLGOMTEVA4XPO3PT/action/replication_record"}},"created_at":"2026-06-19T16:10:56.425570+00:00","updated_at":"2026-06-19T16:10:56.425570+00:00"}