{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:57J3C3NDLTQC573KS46MRTM2RB","short_pith_number":"pith:57J3C3ND","canonical_record":{"source":{"id":"2312.17530","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-29T09:24:26Z","cross_cats_sorted":[],"title_canon_sha256":"94e5815d43977e578f925d64540ed9ea8537de7e21b5405458b2d3b73f265e75","abstract_canon_sha256":"2406b2d4db8a33d1d57dc99ffed3cdb5ca2db0ec1186f85d7475f4b89e1f24ba"},"schema_version":"1.0"},"canonical_sha256":"efd3b16da35ce02eff6a973cc8cd9a887388121e8ec4d1acb69a2f0681b9865d","source":{"kind":"arxiv","id":"2312.17530","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.17530","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"arxiv_version","alias_value":"2312.17530v1","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.17530","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_12","alias_value":"57J3C3NDLTQC","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_16","alias_value":"57J3C3NDLTQC573K","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_8","alias_value":"57J3C3ND","created_at":"2026-07-05T07:28:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:57J3C3NDLTQC573KS46MRTM2RB","target":"record","payload":{"canonical_record":{"source":{"id":"2312.17530","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-29T09:24:26Z","cross_cats_sorted":[],"title_canon_sha256":"94e5815d43977e578f925d64540ed9ea8537de7e21b5405458b2d3b73f265e75","abstract_canon_sha256":"2406b2d4db8a33d1d57dc99ffed3cdb5ca2db0ec1186f85d7475f4b89e1f24ba"},"schema_version":"1.0"},"canonical_sha256":"efd3b16da35ce02eff6a973cc8cd9a887388121e8ec4d1acb69a2f0681b9865d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:28:53.143853Z","signature_b64":"HdlKe41fR2kTeT7nInyIqQCzp+AFPY7bmt2oFMYq+85bgV2iP8TWhr20X4DuBKpMFZi/vgBCYtiMd97dfeUfBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efd3b16da35ce02eff6a973cc8cd9a887388121e8ec4d1acb69a2f0681b9865d","last_reissued_at":"2026-07-05T07:28:53.143434Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:28:53.143434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.17530","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":"2026-07-05T07:28:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d7Bx5Ge9sClO8yGN2aZ0G4KLqKn3qjTZTGM/U19sJQ0FtbMP6Ty6dObBq6uC2EaKRKH/BzfQxbF2obYiwXkeDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:41:28.662609Z"},"content_sha256":"d0cffa73b0263a866b8967c44aaccb5a7dadb20c6cdd5a57a513bf3ac8bdd075","schema_version":"1.0","event_id":"sha256:d0cffa73b0263a866b8967c44aaccb5a7dadb20c6cdd5a57a513bf3ac8bdd075"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:57J3C3NDLTQC573KS46MRTM2RB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Daixun Li, Jitao Ma, Weiying Xie, Yunsong Li, Zixuan Wang","submitted_at":"2023-12-29T09:24:26Z","abstract_excerpt":"Distributed deep learning has recently been attracting more attention in remote sensing (RS) applications due to the challenges posed by the increased amount of open data that are produced daily by Earth observation programs. However, the high communication costs of sending model updates among multiple nodes are a significant bottleneck for scalable distributed learning. Gradient sparsification has been validated as an effective gradient compression (GC) technique for reducing communication costs and thus accelerating the training speed. Existing state-of-the-art gradient sparsification method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.17530","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/2312.17530/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":"2026-07-05T07:28:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x1iY4uw6bXLNefi87PHV8xc1OHYM4hbNHAhLh5Dc0yK6ovqChIwVPMhzR8xHAfH45qnpp2+GTRV0MZVWecSKAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:41:28.662992Z"},"content_sha256":"589bb97171673dd613e4e952e5fc5ffa1783f6f18057152d5f9e27734134da74","schema_version":"1.0","event_id":"sha256:589bb97171673dd613e4e952e5fc5ffa1783f6f18057152d5f9e27734134da74"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/57J3C3NDLTQC573KS46MRTM2RB/bundle.json","state_url":"https://pith.science/pith/57J3C3NDLTQC573KS46MRTM2RB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/57J3C3NDLTQC573KS46MRTM2RB/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":"2026-08-11T13:41:28Z","links":{"resolver":"https://pith.science/pith/57J3C3NDLTQC573KS46MRTM2RB","bundle":"https://pith.science/pith/57J3C3NDLTQC573KS46MRTM2RB/bundle.json","state":"https://pith.science/pith/57J3C3NDLTQC573KS46MRTM2RB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/57J3C3NDLTQC573KS46MRTM2RB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:57J3C3NDLTQC573KS46MRTM2RB","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":"2406b2d4db8a33d1d57dc99ffed3cdb5ca2db0ec1186f85d7475f4b89e1f24ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-29T09:24:26Z","title_canon_sha256":"94e5815d43977e578f925d64540ed9ea8537de7e21b5405458b2d3b73f265e75"},"schema_version":"1.0","source":{"id":"2312.17530","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.17530","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"arxiv_version","alias_value":"2312.17530v1","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.17530","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_12","alias_value":"57J3C3NDLTQC","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_16","alias_value":"57J3C3NDLTQC573K","created_at":"2026-07-05T07:28:53Z"},{"alias_kind":"pith_short_8","alias_value":"57J3C3ND","created_at":"2026-07-05T07:28:53Z"}],"graph_snapshots":[{"event_id":"sha256:589bb97171673dd613e4e952e5fc5ffa1783f6f18057152d5f9e27734134da74","target":"graph","created_at":"2026-07-05T07:28:53Z","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/2312.17530/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed deep learning has recently been attracting more attention in remote sensing (RS) applications due to the challenges posed by the increased amount of open data that are produced daily by Earth observation programs. However, the high communication costs of sending model updates among multiple nodes are a significant bottleneck for scalable distributed learning. Gradient sparsification has been validated as an effective gradient compression (GC) technique for reducing communication costs and thus accelerating the training speed. Existing state-of-the-art gradient sparsification method","authors_text":"Daixun Li, Jitao Ma, Weiying Xie, Yunsong Li, Zixuan Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-29T09:24:26Z","title":"RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.17530","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:d0cffa73b0263a866b8967c44aaccb5a7dadb20c6cdd5a57a513bf3ac8bdd075","target":"record","created_at":"2026-07-05T07:28:53Z","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":"2406b2d4db8a33d1d57dc99ffed3cdb5ca2db0ec1186f85d7475f4b89e1f24ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-29T09:24:26Z","title_canon_sha256":"94e5815d43977e578f925d64540ed9ea8537de7e21b5405458b2d3b73f265e75"},"schema_version":"1.0","source":{"id":"2312.17530","kind":"arxiv","version":1}},"canonical_sha256":"efd3b16da35ce02eff6a973cc8cd9a887388121e8ec4d1acb69a2f0681b9865d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"efd3b16da35ce02eff6a973cc8cd9a887388121e8ec4d1acb69a2f0681b9865d","first_computed_at":"2026-07-05T07:28:53.143434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:28:53.143434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HdlKe41fR2kTeT7nInyIqQCzp+AFPY7bmt2oFMYq+85bgV2iP8TWhr20X4DuBKpMFZi/vgBCYtiMd97dfeUfBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:28:53.143853Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.17530","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0cffa73b0263a866b8967c44aaccb5a7dadb20c6cdd5a57a513bf3ac8bdd075","sha256:589bb97171673dd613e4e952e5fc5ffa1783f6f18057152d5f9e27734134da74"],"state_sha256":"08e2a84dd0599e0d3caf7f7e2a69650136e6058f06dba888a6a27287b3413fe7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MnXgVnHmupRuNUAXmM01Ei2davvybFYdyrPALRyY9U3tdcwEIhRG1sr7QTJcarJe/zuoXeLPcT7uG3M/xQ+FCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T13:41:28.666398Z","bundle_sha256":"7c6991497cd2802e4b025e74409783b2dbdb5aac2ffc54205b3c727f0ee52b65"}}