{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WTG3WNGTXCCWZF3QXEAB5UGG5J","short_pith_number":"pith:WTG3WNGT","canonical_record":{"source":{"id":"2501.07984","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-14T10:09:55Z","cross_cats_sorted":[],"title_canon_sha256":"3ed33bb322124a5fcff0cd031555b9eac4f63d4a5a213d2596891f118e489125","abstract_canon_sha256":"17080bbd96a4eda38dbb8a61723dc05616fae02b09e4698e1199954111899aa8"},"schema_version":"1.0"},"canonical_sha256":"b4cdbb34d3b8856c9770b9001ed0c6ea70b047ad7d52e3f4a5d8985a10e923e1","source":{"kind":"arxiv","id":"2501.07984","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.07984","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"arxiv_version","alias_value":"2501.07984v1","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.07984","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_12","alias_value":"WTG3WNGTXCCW","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_16","alias_value":"WTG3WNGTXCCWZF3Q","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_8","alias_value":"WTG3WNGT","created_at":"2026-07-05T10:00:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WTG3WNGTXCCWZF3QXEAB5UGG5J","target":"record","payload":{"canonical_record":{"source":{"id":"2501.07984","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-14T10:09:55Z","cross_cats_sorted":[],"title_canon_sha256":"3ed33bb322124a5fcff0cd031555b9eac4f63d4a5a213d2596891f118e489125","abstract_canon_sha256":"17080bbd96a4eda38dbb8a61723dc05616fae02b09e4698e1199954111899aa8"},"schema_version":"1.0"},"canonical_sha256":"b4cdbb34d3b8856c9770b9001ed0c6ea70b047ad7d52e3f4a5d8985a10e923e1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:53.376594Z","signature_b64":"evoVHnr1Sg3kUrn95vPsRvadedGPznxD2tEKjqGM+UbLEbcxoj9DeRyYSAkP3YywjpUIu4EkIpPQHSNBykOZAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4cdbb34d3b8856c9770b9001ed0c6ea70b047ad7d52e3f4a5d8985a10e923e1","last_reissued_at":"2026-07-05T10:00:53.375965Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:53.375965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.07984","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":"2026-07-05T10:00:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dtUQ/isSPRYtJ73nnkeZGnEsluyv8gA/iz8JNnV1bIx7tnXphDiAlUNezsTpY8ng4CJBqKJnxOEu9HS/3gRMCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T10:19:12.186138Z"},"content_sha256":"ea13b112a9661347ac2f710880da7f01df6309a2fb20da80a0015b8d0dba5f12","schema_version":"1.0","event_id":"sha256:ea13b112a9661347ac2f710880da7f01df6309a2fb20da80a0015b8d0dba5f12"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WTG3WNGTXCCWZF3QXEAB5UGG5J","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Threshold Attention Network for Semantic Segmentation of Remote Sensing Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Wei Long, Xuexue Zhang, Yongjun Zhang, Yujie Xu, Zhongwei Cui","submitted_at":"2025-01-14T10:09:55Z","abstract_excerpt":"Semantic segmentation of remote sensing images is essential for various applications, including vegetation monitoring, disaster management, and urban planning. Previous studies have demonstrated that the self-attention mechanism (SA) is an effective approach for designing segmentation networks that can capture long-range pixel dependencies. SA enables the network to model the global dependencies between the input features, resulting in improved segmentation outcomes. However, the high density of attentional feature maps used in this mechanism causes exponential increases in computational compl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.07984","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/2501.07984/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":"2026-07-05T10:00:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yBRuKR2uTua03MHi/nKHy4yXBxDOv4lyswq2mEFZRW2Wn2brHDs41mW0dRcAK2HVrYobzbgfeWbGecDPdu/nAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T10:19:12.186646Z"},"content_sha256":"a133afa80eac028e1e7799d4f848659dc94f2b1171d5d38dc7abf994ecd318c4","schema_version":"1.0","event_id":"sha256:a133afa80eac028e1e7799d4f848659dc94f2b1171d5d38dc7abf994ecd318c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/bundle.json","state_url":"https://pith.science/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/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":"2026-08-22T10:19:12Z","links":{"resolver":"https://pith.science/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J","bundle":"https://pith.science/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/bundle.json","state":"https://pith.science/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WTG3WNGTXCCWZF3QXEAB5UGG5J/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WTG3WNGTXCCWZF3QXEAB5UGG5J","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":"17080bbd96a4eda38dbb8a61723dc05616fae02b09e4698e1199954111899aa8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-14T10:09:55Z","title_canon_sha256":"3ed33bb322124a5fcff0cd031555b9eac4f63d4a5a213d2596891f118e489125"},"schema_version":"1.0","source":{"id":"2501.07984","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.07984","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"arxiv_version","alias_value":"2501.07984v1","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.07984","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_12","alias_value":"WTG3WNGTXCCW","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_16","alias_value":"WTG3WNGTXCCWZF3Q","created_at":"2026-07-05T10:00:53Z"},{"alias_kind":"pith_short_8","alias_value":"WTG3WNGT","created_at":"2026-07-05T10:00:53Z"}],"graph_snapshots":[{"event_id":"sha256:a133afa80eac028e1e7799d4f848659dc94f2b1171d5d38dc7abf994ecd318c4","target":"graph","created_at":"2026-07-05T10:00:53Z","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/2501.07984/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic segmentation of remote sensing images is essential for various applications, including vegetation monitoring, disaster management, and urban planning. Previous studies have demonstrated that the self-attention mechanism (SA) is an effective approach for designing segmentation networks that can capture long-range pixel dependencies. SA enables the network to model the global dependencies between the input features, resulting in improved segmentation outcomes. However, the high density of attentional feature maps used in this mechanism causes exponential increases in computational compl","authors_text":"Wei Long, Xuexue Zhang, Yongjun Zhang, Yujie Xu, Zhongwei Cui","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-14T10:09:55Z","title":"Threshold Attention Network for Semantic Segmentation of Remote Sensing Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.07984","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:ea13b112a9661347ac2f710880da7f01df6309a2fb20da80a0015b8d0dba5f12","target":"record","created_at":"2026-07-05T10:00:53Z","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":"17080bbd96a4eda38dbb8a61723dc05616fae02b09e4698e1199954111899aa8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-14T10:09:55Z","title_canon_sha256":"3ed33bb322124a5fcff0cd031555b9eac4f63d4a5a213d2596891f118e489125"},"schema_version":"1.0","source":{"id":"2501.07984","kind":"arxiv","version":1}},"canonical_sha256":"b4cdbb34d3b8856c9770b9001ed0c6ea70b047ad7d52e3f4a5d8985a10e923e1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b4cdbb34d3b8856c9770b9001ed0c6ea70b047ad7d52e3f4a5d8985a10e923e1","first_computed_at":"2026-07-05T10:00:53.375965Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:00:53.375965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"evoVHnr1Sg3kUrn95vPsRvadedGPznxD2tEKjqGM+UbLEbcxoj9DeRyYSAkP3YywjpUIu4EkIpPQHSNBykOZAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:00:53.376594Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.07984","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ea13b112a9661347ac2f710880da7f01df6309a2fb20da80a0015b8d0dba5f12","sha256:a133afa80eac028e1e7799d4f848659dc94f2b1171d5d38dc7abf994ecd318c4"],"state_sha256":"862a55836ea5943952f99ac9a3171dd72c73e683bb0fe305954fb347dc86125d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iGUBtyv13kLtoMYitbulVXanktYDF8KeXOveovsJqT+7aOtV7FuD2ahBNfeon8MtT1uWpabCefbRklel5skKBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T10:19:12.192025Z","bundle_sha256":"54af92181ea00f75bfe387a27d537f924d0932dc1ea275acd082faa18c12e89b"}}