{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Y47IQFEO6X5474DRCDCIKB25O7","short_pith_number":"pith:Y47IQFEO","canonical_record":{"source":{"id":"2508.09085","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-12T17:07:27Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"0b23114178c1228cdd853c351685fc53bb1b7890bb70e9eb5bd4a715e1939882","abstract_canon_sha256":"0c278a35eb73c448ea680f7c4badc5309f036f51fcbfc20e383af5097ab2508d"},"schema_version":"1.0"},"canonical_sha256":"c73e88148ef5fbcff07110c485075d77c757856f59b7142e66093e935effd601","source":{"kind":"arxiv","id":"2508.09085","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09085","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09085v1","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09085","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_12","alias_value":"Y47IQFEO6X54","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_16","alias_value":"Y47IQFEO6X5474DR","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_8","alias_value":"Y47IQFEO","created_at":"2026-07-05T11:52:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Y47IQFEO6X5474DRCDCIKB25O7","target":"record","payload":{"canonical_record":{"source":{"id":"2508.09085","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-12T17:07:27Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"0b23114178c1228cdd853c351685fc53bb1b7890bb70e9eb5bd4a715e1939882","abstract_canon_sha256":"0c278a35eb73c448ea680f7c4badc5309f036f51fcbfc20e383af5097ab2508d"},"schema_version":"1.0"},"canonical_sha256":"c73e88148ef5fbcff07110c485075d77c757856f59b7142e66093e935effd601","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:39.547912Z","signature_b64":"gaONseMPxN9k594yOgregCRDYEFW4p3odROnyq3FXi/uS+YtCIitKdTQZxvR8nVBGXTMtlkQarXVjEMs9792Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c73e88148ef5fbcff07110c485075d77c757856f59b7142e66093e935effd601","last_reissued_at":"2026-07-05T11:52:39.547423Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:39.547423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.09085","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:52:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XI1FsFKQuJ/CeBeDpUC7vGZ1DbO1IQxwfigz8O6c6oaPKJpyqESgXvKgC7P90Ap6l0OFg6/1HD6oZ1Btn5YgCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:08:15.194979Z"},"content_sha256":"58b0f1039cdfcd6cc082f475da3cec236c601560bae4552f01475f13ac26a77a","schema_version":"1.0","event_id":"sha256:58b0f1039cdfcd6cc082f475da3cec236c601560bae4552f01475f13ac26a77a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Y47IQFEO6X5474DRCDCIKB25O7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.NI","authors_text":"Senkang Hu, Xianhao Chen, Yihang Tao, Yiqin Deng, Yuguang Fang, Zheng Lin, Zihan Fang","submitted_at":"2025-08-12T17:07:27Z","abstract_excerpt":"Outdoor health monitoring is essential to detect early abnormal health status for safeguarding human health and safety. Conventional outdoor monitoring relies on static multimodal deep learning frameworks, which requires extensive data training from scratch and fails to capture subtle health status changes. Multimodal large language models (MLLMs) emerge as a promising alternative, utilizing only small datasets to fine-tune pre-trained information-rich models for enabling powerful health status monitoring. Unfortunately, MLLM-based outdoor health monitoring also faces significant challenges: I"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09085","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/2508.09085/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:52:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vUHW6Jvax5WWdfDep3YMybqU4J8o5kiBOjRU8bXs4fVsfmXQjeDn2i0iiBKU6ODQvqZ9lCFj5WR0x+7rUIZ9CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:08:15.195972Z"},"content_sha256":"492849e262d30b4b3a52269686c0b0e726ce6b641bb65a0db74aa443e3e18ff6","schema_version":"1.0","event_id":"sha256:492849e262d30b4b3a52269686c0b0e726ce6b641bb65a0db74aa443e3e18ff6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y47IQFEO6X5474DRCDCIKB25O7/bundle.json","state_url":"https://pith.science/pith/Y47IQFEO6X5474DRCDCIKB25O7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y47IQFEO6X5474DRCDCIKB25O7/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T18:08:15Z","links":{"resolver":"https://pith.science/pith/Y47IQFEO6X5474DRCDCIKB25O7","bundle":"https://pith.science/pith/Y47IQFEO6X5474DRCDCIKB25O7/bundle.json","state":"https://pith.science/pith/Y47IQFEO6X5474DRCDCIKB25O7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y47IQFEO6X5474DRCDCIKB25O7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Y47IQFEO6X5474DRCDCIKB25O7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0c278a35eb73c448ea680f7c4badc5309f036f51fcbfc20e383af5097ab2508d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-12T17:07:27Z","title_canon_sha256":"0b23114178c1228cdd853c351685fc53bb1b7890bb70e9eb5bd4a715e1939882"},"schema_version":"1.0","source":{"id":"2508.09085","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09085","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09085v1","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09085","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_12","alias_value":"Y47IQFEO6X54","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_16","alias_value":"Y47IQFEO6X5474DR","created_at":"2026-07-05T11:52:39Z"},{"alias_kind":"pith_short_8","alias_value":"Y47IQFEO","created_at":"2026-07-05T11:52:39Z"}],"graph_snapshots":[{"event_id":"sha256:492849e262d30b4b3a52269686c0b0e726ce6b641bb65a0db74aa443e3e18ff6","target":"graph","created_at":"2026-07-05T11:52:39Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2508.09085/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Outdoor health monitoring is essential to detect early abnormal health status for safeguarding human health and safety. Conventional outdoor monitoring relies on static multimodal deep learning frameworks, which requires extensive data training from scratch and fails to capture subtle health status changes. Multimodal large language models (MLLMs) emerge as a promising alternative, utilizing only small datasets to fine-tune pre-trained information-rich models for enabling powerful health status monitoring. Unfortunately, MLLM-based outdoor health monitoring also faces significant challenges: I","authors_text":"Senkang Hu, Xianhao Chen, Yihang Tao, Yiqin Deng, Yuguang Fang, Zheng Lin, Zihan Fang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-12T17:07:27Z","title":"Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09085","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:58b0f1039cdfcd6cc082f475da3cec236c601560bae4552f01475f13ac26a77a","target":"record","created_at":"2026-07-05T11:52:39Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0c278a35eb73c448ea680f7c4badc5309f036f51fcbfc20e383af5097ab2508d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-12T17:07:27Z","title_canon_sha256":"0b23114178c1228cdd853c351685fc53bb1b7890bb70e9eb5bd4a715e1939882"},"schema_version":"1.0","source":{"id":"2508.09085","kind":"arxiv","version":1}},"canonical_sha256":"c73e88148ef5fbcff07110c485075d77c757856f59b7142e66093e935effd601","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c73e88148ef5fbcff07110c485075d77c757856f59b7142e66093e935effd601","first_computed_at":"2026-07-05T11:52:39.547423Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:52:39.547423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gaONseMPxN9k594yOgregCRDYEFW4p3odROnyq3FXi/uS+YtCIitKdTQZxvR8nVBGXTMtlkQarXVjEMs9792Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T11:52:39.547912Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.09085","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:58b0f1039cdfcd6cc082f475da3cec236c601560bae4552f01475f13ac26a77a","sha256:492849e262d30b4b3a52269686c0b0e726ce6b641bb65a0db74aa443e3e18ff6"],"state_sha256":"0c4dde6fb7459443b3b51a9824d70c0c80e1bff2021c17fc69d3290d328a59e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RmalSd4gwJlzTs9NagYbjDlzm1mRX6jggHYGa6kPQtPp3l168M7wYIJgSSe12MKKt8o8wDVamU02wtgDbsAmAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T18:08:15.201457Z","bundle_sha256":"b13eca8ed94bcdd9c538bfb5144e90d3dc08c25209394bc94003104b290ad234"}}