{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WTNWKSYTV2EGEFABIFLNO3RF2O","short_pith_number":"pith:WTNWKSYT","schema_version":"1.0","canonical_sha256":"b4db654b13ae886214014156d76e25d390c80816a62351543c67096e308bd06c","source":{"kind":"arxiv","id":"2605.29861","version":1},"attestation_state":"computed","paper":{"title":"Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chenghao Zhang, Guanting Dong, Tong Zhao, Yufan Liu, Zhicheng Dou","submitted_at":"2026-05-28T12:40:34Z","abstract_excerpt":"Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthesizes scattered evidence into long-form reports. However, verifiable multimodal deep research remains challenging due to open-ended synthesis without deterministic ground truth and the need to interleave textual arguments with visual evidence. We propose \\textsc{Ptah}, a multi-agent harness for interleaved report generation. \\textsc{Ptah} orchestrates the lifecycle from user query to rendered web report through planning, research, and writing sta"},"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":"2605.29861","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T12:40:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"55a1c33fcccb8e52053cd9f9a86ee2bf0187c2e636172a560cfd4905dfe7b51d","abstract_canon_sha256":"f96175cd7ebeb77140ef7ea854d1d9b4728415dc20b61accd099fe4e5f1eca68"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:05:56.612708Z","signature_b64":"gdOK2PMcvid3jV92x0jzd2UZazOKSeRzyrWIkXpL1JditSJE2F4a9JSv/AaloBKM8pqUceKPXiAOqzyml/1fAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4db654b13ae886214014156d76e25d390c80816a62351543c67096e308bd06c","last_reissued_at":"2026-05-29T02:05:56.611949Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:05:56.611949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chenghao Zhang, Guanting Dong, Tong Zhao, Yufan Liu, Zhicheng Dou","submitted_at":"2026-05-28T12:40:34Z","abstract_excerpt":"Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthesizes scattered evidence into long-form reports. However, verifiable multimodal deep research remains challenging due to open-ended synthesis without deterministic ground truth and the need to interleave textual arguments with visual evidence. We propose \\textsc{Ptah}, a multi-agent harness for interleaved report generation. \\textsc{Ptah} orchestrates the lifecycle from user query to rendered web report through planning, research, and writing sta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29861","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/2605.29861/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":"2605.29861","created_at":"2026-05-29T02:05:56.612078+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.29861v1","created_at":"2026-05-29T02:05:56.612078+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29861","created_at":"2026-05-29T02:05:56.612078+00:00"},{"alias_kind":"pith_short_12","alias_value":"WTNWKSYTV2EG","created_at":"2026-05-29T02:05:56.612078+00:00"},{"alias_kind":"pith_short_16","alias_value":"WTNWKSYTV2EGEFAB","created_at":"2026-05-29T02:05:56.612078+00:00"},{"alias_kind":"pith_short_8","alias_value":"WTNWKSYT","created_at":"2026-05-29T02:05:56.612078+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/WTNWKSYTV2EGEFABIFLNO3RF2O","json":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O.json","graph_json":"https://pith.science/api/pith-number/WTNWKSYTV2EGEFABIFLNO3RF2O/graph.json","events_json":"https://pith.science/api/pith-number/WTNWKSYTV2EGEFABIFLNO3RF2O/events.json","paper":"https://pith.science/paper/WTNWKSYT"},"agent_actions":{"view_html":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O","download_json":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O.json","view_paper":"https://pith.science/paper/WTNWKSYT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.29861&json=true","fetch_graph":"https://pith.science/api/pith-number/WTNWKSYTV2EGEFABIFLNO3RF2O/graph.json","fetch_events":"https://pith.science/api/pith-number/WTNWKSYTV2EGEFABIFLNO3RF2O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O/action/storage_attestation","attest_author":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O/action/author_attestation","sign_citation":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O/action/citation_signature","submit_replication":"https://pith.science/pith/WTNWKSYTV2EGEFABIFLNO3RF2O/action/replication_record"}},"created_at":"2026-05-29T02:05:56.612078+00:00","updated_at":"2026-05-29T02:05:56.612078+00:00"}