{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:V4QRDPJEYS2PXP7OHMVW5AI755","short_pith_number":"pith:V4QRDPJE","schema_version":"1.0","canonical_sha256":"af2111bd24c4b4fbbfee3b2b6e811fef7150f99ca614d107f8eb42f6b97cffc5","source":{"kind":"arxiv","id":"2606.09110","version":1},"attestation_state":"computed","paper":{"title":"HDRAgent: An Agentic Framework for Multi-Exposure HDR Imaging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qingsen Yan, Ruixing Wang, Tao Hu, Weiyu Zhou, Xiaogang Xu, Yijian Wang","submitted_at":"2026-06-08T07:00:56Z","abstract_excerpt":"Most existing multi-exposure HDR methods follow a fixed feed-forward reconstruction paradigm, making them prone to ghosting artifacts in complex dynamic scenes. To address this issue, we propose HDRAgent, the first agent-driven framework for HDR imaging, which adaptively selects reconstruction strategies according to the current scene conditions. Specifically, to provide scene-specific prior knowledge, we introduce a fine-grained contextual knowledge matching (FCM) module. This module leverages multimodal large language model (MLLM)-derived scene perception to retrieve relevant historical case"},"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":"2606.09110","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:00:56Z","cross_cats_sorted":[],"title_canon_sha256":"d67786ca7900257b296db628a7d087b0817f8e463fec177af935e352743a9b1d","abstract_canon_sha256":"784f1dfda836d9cb443a77d13f974851e93451760b7b29c15bf5a1f7c80b287b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:07:59.653159Z","signature_b64":"E93M36qFSL+B7LDXm3Jnk17B1lqdhTSIkdkvNaez0tgd7y6PeedTcETCd1PEAyQgmUCzMhWh6NTItSOtuHRfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af2111bd24c4b4fbbfee3b2b6e811fef7150f99ca614d107f8eb42f6b97cffc5","last_reissued_at":"2026-06-09T02:07:59.652135Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:07:59.652135Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"HDRAgent: An Agentic Framework for Multi-Exposure HDR Imaging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qingsen Yan, Ruixing Wang, Tao Hu, Weiyu Zhou, Xiaogang Xu, Yijian Wang","submitted_at":"2026-06-08T07:00:56Z","abstract_excerpt":"Most existing multi-exposure HDR methods follow a fixed feed-forward reconstruction paradigm, making them prone to ghosting artifacts in complex dynamic scenes. To address this issue, we propose HDRAgent, the first agent-driven framework for HDR imaging, which adaptively selects reconstruction strategies according to the current scene conditions. Specifically, to provide scene-specific prior knowledge, we introduce a fine-grained contextual knowledge matching (FCM) module. This module leverages multimodal large language model (MLLM)-derived scene perception to retrieve relevant historical case"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09110","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/2606.09110/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":"2606.09110","created_at":"2026-06-09T02:07:59.652277+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.09110v1","created_at":"2026-06-09T02:07:59.652277+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09110","created_at":"2026-06-09T02:07:59.652277+00:00"},{"alias_kind":"pith_short_12","alias_value":"V4QRDPJEYS2P","created_at":"2026-06-09T02:07:59.652277+00:00"},{"alias_kind":"pith_short_16","alias_value":"V4QRDPJEYS2PXP7O","created_at":"2026-06-09T02:07:59.652277+00:00"},{"alias_kind":"pith_short_8","alias_value":"V4QRDPJE","created_at":"2026-06-09T02:07:59.652277+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/V4QRDPJEYS2PXP7OHMVW5AI755","json":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755.json","graph_json":"https://pith.science/api/pith-number/V4QRDPJEYS2PXP7OHMVW5AI755/graph.json","events_json":"https://pith.science/api/pith-number/V4QRDPJEYS2PXP7OHMVW5AI755/events.json","paper":"https://pith.science/paper/V4QRDPJE"},"agent_actions":{"view_html":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755","download_json":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755.json","view_paper":"https://pith.science/paper/V4QRDPJE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.09110&json=true","fetch_graph":"https://pith.science/api/pith-number/V4QRDPJEYS2PXP7OHMVW5AI755/graph.json","fetch_events":"https://pith.science/api/pith-number/V4QRDPJEYS2PXP7OHMVW5AI755/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755/action/storage_attestation","attest_author":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755/action/author_attestation","sign_citation":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755/action/citation_signature","submit_replication":"https://pith.science/pith/V4QRDPJEYS2PXP7OHMVW5AI755/action/replication_record"}},"created_at":"2026-06-09T02:07:59.652277+00:00","updated_at":"2026-06-09T02:07:59.652277+00:00"}