{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:G5Q62MA2UWWEJPR7YF54Q7CKQQ","short_pith_number":"pith:G5Q62MA2","canonical_record":{"source":{"id":"2605.28174","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T08:55:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ea95756ab4c79fc5eeda0466a2976f76091f88c9c8e6e67ebf3140833e7acc58","abstract_canon_sha256":"1b2fb49c8af682d97823dc3dfd4b2bd4aed63435466cad9d3ea7b79079a2b289"},"schema_version":"1.0"},"canonical_sha256":"3761ed301aa5ac44be3fc17bc87c4a843bb382b62ea3b608c2996cb160727db5","source":{"kind":"arxiv","id":"2605.28174","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28174","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28174v1","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28174","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_12","alias_value":"G5Q62MA2UWWE","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_16","alias_value":"G5Q62MA2UWWEJPR7","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_8","alias_value":"G5Q62MA2","created_at":"2026-05-28T01:05:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:G5Q62MA2UWWEJPR7YF54Q7CKQQ","target":"record","payload":{"canonical_record":{"source":{"id":"2605.28174","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T08:55:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ea95756ab4c79fc5eeda0466a2976f76091f88c9c8e6e67ebf3140833e7acc58","abstract_canon_sha256":"1b2fb49c8af682d97823dc3dfd4b2bd4aed63435466cad9d3ea7b79079a2b289"},"schema_version":"1.0"},"canonical_sha256":"3761ed301aa5ac44be3fc17bc87c4a843bb382b62ea3b608c2996cb160727db5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T01:05:01.247522Z","signature_b64":"5+d2R8jDpOdgzBCWEWHD0ASbBeFb4C9Si3QYYcyKY9NZ+X5xdCqS+b5nR2VGM42jlgiBvgUy9q4mY93WPRFIBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3761ed301aa5ac44be3fc17bc87c4a843bb382b62ea3b608c2996cb160727db5","last_reissued_at":"2026-05-28T01:05:01.247031Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T01:05:01.247031Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.28174","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":"2026-05-28T01:05:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R00QyAAMgn4IFYPxiMNRzaBmZ33ZDeGM3q6PRBW4Ftrudq9PtUT1UCe3MkHhMorXC+NI1Rd5hiADwJBJu8S/DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T08:06:48.883185Z"},"content_sha256":"e5254e3aa37296a07094c4fa0895c21201a5e6c661983b1e80bbee586b9b4b82","schema_version":"1.0","event_id":"sha256:e5254e3aa37296a07094c4fa0895c21201a5e6c661983b1e80bbee586b9b4b82"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:G5Q62MA2UWWEJPR7YF54Q7CKQQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and Scales","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Areej Alwahas, Bernard Ghanem, Fernando T. Maestre, Fida Mohammad Thoker, Jorge L. Rodriguez, Kasper Johansen, Mariana Elias Lara, Matthew F. McCabe, Victor Angulo Morales","submitted_at":"2026-05-27T08:55:54Z","abstract_excerpt":"Foundation models offer a promising route to transferable remote sensing representations, but many current approaches depend on very large pretraining datasets and fixed sensor configurations, limiting their suitability for ecological and environmental applications, where observations often vary across platforms, spatial and spectral resolutions, and available modalities. We introduce FLORO, a multimodal geospatial foundation model designed to learn transferable representations from a small but highly diverse remote sensing corpus. FLORO is pretrained using masked autoencoding on a heterogeneo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28174","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/2605.28174/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":"2026-05-28T01:05:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i/WzISDcuyq9Kl60LvrwpzITKAU7aVvMTBX5e3wHTwDRpmGGC8GuHLdXHQ+lTU2ppK1fj5gihzuFzs1CuttGCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T08:06:48.883578Z"},"content_sha256":"4b59bb16d810fed1de8b946320e5ed257f70363cb686f2b2083716a6a8d16c5e","schema_version":"1.0","event_id":"sha256:4b59bb16d810fed1de8b946320e5ed257f70363cb686f2b2083716a6a8d16c5e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/bundle.json","state_url":"https://pith.science/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/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":"2026-06-28T08:06:48Z","links":{"resolver":"https://pith.science/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ","bundle":"https://pith.science/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/bundle.json","state":"https://pith.science/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G5Q62MA2UWWEJPR7YF54Q7CKQQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:G5Q62MA2UWWEJPR7YF54Q7CKQQ","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":"1b2fb49c8af682d97823dc3dfd4b2bd4aed63435466cad9d3ea7b79079a2b289","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T08:55:54Z","title_canon_sha256":"ea95756ab4c79fc5eeda0466a2976f76091f88c9c8e6e67ebf3140833e7acc58"},"schema_version":"1.0","source":{"id":"2605.28174","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28174","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28174v1","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28174","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_12","alias_value":"G5Q62MA2UWWE","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_16","alias_value":"G5Q62MA2UWWEJPR7","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_8","alias_value":"G5Q62MA2","created_at":"2026-05-28T01:05:01Z"}],"graph_snapshots":[{"event_id":"sha256:4b59bb16d810fed1de8b946320e5ed257f70363cb686f2b2083716a6a8d16c5e","target":"graph","created_at":"2026-05-28T01:05:01Z","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/2605.28174/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Foundation models offer a promising route to transferable remote sensing representations, but many current approaches depend on very large pretraining datasets and fixed sensor configurations, limiting their suitability for ecological and environmental applications, where observations often vary across platforms, spatial and spectral resolutions, and available modalities. We introduce FLORO, a multimodal geospatial foundation model designed to learn transferable representations from a small but highly diverse remote sensing corpus. FLORO is pretrained using masked autoencoding on a heterogeneo","authors_text":"Areej Alwahas, Bernard Ghanem, Fernando T. Maestre, Fida Mohammad Thoker, Jorge L. Rodriguez, Kasper Johansen, Mariana Elias Lara, Matthew F. McCabe, Victor Angulo Morales","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T08:55:54Z","title":"FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and Scales"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28174","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:e5254e3aa37296a07094c4fa0895c21201a5e6c661983b1e80bbee586b9b4b82","target":"record","created_at":"2026-05-28T01:05:01Z","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":"1b2fb49c8af682d97823dc3dfd4b2bd4aed63435466cad9d3ea7b79079a2b289","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T08:55:54Z","title_canon_sha256":"ea95756ab4c79fc5eeda0466a2976f76091f88c9c8e6e67ebf3140833e7acc58"},"schema_version":"1.0","source":{"id":"2605.28174","kind":"arxiv","version":1}},"canonical_sha256":"3761ed301aa5ac44be3fc17bc87c4a843bb382b62ea3b608c2996cb160727db5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3761ed301aa5ac44be3fc17bc87c4a843bb382b62ea3b608c2996cb160727db5","first_computed_at":"2026-05-28T01:05:01.247031Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:05:01.247031Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5+d2R8jDpOdgzBCWEWHD0ASbBeFb4C9Si3QYYcyKY9NZ+X5xdCqS+b5nR2VGM42jlgiBvgUy9q4mY93WPRFIBA==","signature_status":"signed_v1","signed_at":"2026-05-28T01:05:01.247522Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.28174","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e5254e3aa37296a07094c4fa0895c21201a5e6c661983b1e80bbee586b9b4b82","sha256:4b59bb16d810fed1de8b946320e5ed257f70363cb686f2b2083716a6a8d16c5e"],"state_sha256":"21f51999b53bb8a6a152580db049fc923f4f86fb7707119c3f20413d63b17d11"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sOnbiTU3U2utHbaLy3NC3chzGaUB7lt/NB9IshRVqQn+z4By0Ii2vJAkrWEZe93XCJ+T4ay8sJeUi6mqwSOxDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T08:06:48.885689Z","bundle_sha256":"edc1bb5eb1517dcf405a4aec2b062d97af27e435d57bb78849ed00a09d517173"}}