{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:FLBNVJTSC4ZO5F5C25EK7IH6J7","short_pith_number":"pith:FLBNVJTS","canonical_record":{"source":{"id":"2506.17944","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-22T08:40:56Z","cross_cats_sorted":[],"title_canon_sha256":"7defb1678fc7035bc665a41e8d1a5c2acdd5186bc485abfca582df63068dc2b0","abstract_canon_sha256":"4c15318f7c1fa6abd8693674ba5272fa8c2a6da1b1eae51023bf61186a44d6dd"},"schema_version":"1.0"},"canonical_sha256":"2ac2daa6721732ee97a2d748afa0fe4fd1f643c4b96396d2893651d6877d0d2b","source":{"kind":"arxiv","id":"2506.17944","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.17944","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"arxiv_version","alias_value":"2506.17944v2","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.17944","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_12","alias_value":"FLBNVJTSC4ZO","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_16","alias_value":"FLBNVJTSC4ZO5F5C","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_8","alias_value":"FLBNVJTS","created_at":"2026-07-05T11:28:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:FLBNVJTSC4ZO5F5C25EK7IH6J7","target":"record","payload":{"canonical_record":{"source":{"id":"2506.17944","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-22T08:40:56Z","cross_cats_sorted":[],"title_canon_sha256":"7defb1678fc7035bc665a41e8d1a5c2acdd5186bc485abfca582df63068dc2b0","abstract_canon_sha256":"4c15318f7c1fa6abd8693674ba5272fa8c2a6da1b1eae51023bf61186a44d6dd"},"schema_version":"1.0"},"canonical_sha256":"2ac2daa6721732ee97a2d748afa0fe4fd1f643c4b96396d2893651d6877d0d2b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:28:17.762124Z","signature_b64":"0jmzyYfuCW4pvcfO4rvlwnxYTA06TwI81sa1Jde9ZqgpDX1ldUny7Zby0y6v4uUqESXKpxZx0Y81UIf5N5wABA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2ac2daa6721732ee97a2d748afa0fe4fd1f643c4b96396d2893651d6877d0d2b","last_reissued_at":"2026-07-05T11:28:17.761643Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:28:17.761643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.17944","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:28:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Oi3ACW+Q0xrfTwMidEYW4yYg+49BWOxJ0IokGIrgHd5ftE6fgjpRh/NHBrnJAP36jmsWOG9CRKEu3wpr0rLaDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T02:34:31.702337Z"},"content_sha256":"8be8bf31f68f5c296f22cdf58457e9d7bc3a8cc4f0681f6c643c1c20a368377e","schema_version":"1.0","event_id":"sha256:8be8bf31f68f5c296f22cdf58457e9d7bc3a8cc4f0681f6c643c1c20a368377e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:FLBNVJTSC4ZO5F5C25EK7IH6J7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SegChange-R1: LLM-Augmented Remote Sensing Change Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fei Zhou","submitted_at":"2025-06-22T08:40:56Z","abstract_excerpt":"Remote sensing change detection is used in urban planning, terrain analysis, and environmental monitoring by analyzing feature changes in the same area over time. In this paper, we propose a large language model (LLM) augmented inference approach (SegChange-R1), which enhances the detection capability by integrating textual descriptive information and guides the model to focus on relevant change regions, accelerating convergence. We designed a linear attention-based spatial transformation module (BEV) to address modal misalignment by unifying features from different times into a BEV space. Fur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.17944","kind":"arxiv","version":2},"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/2506.17944/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":"2026-07-05T11:28:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GvcsRPaJNkvlNIMgTrcTnpb5FOnSyvOvo+K+hIFYiWCTQ3R8zeGOVO3faI0J77Wn80Z4hlWKG+s1t/jRC2W8Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T02:34:31.703276Z"},"content_sha256":"8951f86814c25e436b90ab50afa7390291ce49a28b87f90979a242e452b6af61","schema_version":"1.0","event_id":"sha256:8951f86814c25e436b90ab50afa7390291ce49a28b87f90979a242e452b6af61"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/bundle.json","state_url":"https://pith.science/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/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":"2026-08-07T02:34:31Z","links":{"resolver":"https://pith.science/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7","bundle":"https://pith.science/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/bundle.json","state":"https://pith.science/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FLBNVJTSC4ZO5F5C25EK7IH6J7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FLBNVJTSC4ZO5F5C25EK7IH6J7","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":"4c15318f7c1fa6abd8693674ba5272fa8c2a6da1b1eae51023bf61186a44d6dd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-22T08:40:56Z","title_canon_sha256":"7defb1678fc7035bc665a41e8d1a5c2acdd5186bc485abfca582df63068dc2b0"},"schema_version":"1.0","source":{"id":"2506.17944","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.17944","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"arxiv_version","alias_value":"2506.17944v2","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.17944","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_12","alias_value":"FLBNVJTSC4ZO","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_16","alias_value":"FLBNVJTSC4ZO5F5C","created_at":"2026-07-05T11:28:17Z"},{"alias_kind":"pith_short_8","alias_value":"FLBNVJTS","created_at":"2026-07-05T11:28:17Z"}],"graph_snapshots":[{"event_id":"sha256:8951f86814c25e436b90ab50afa7390291ce49a28b87f90979a242e452b6af61","target":"graph","created_at":"2026-07-05T11:28:17Z","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/2506.17944/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Remote sensing change detection is used in urban planning, terrain analysis, and environmental monitoring by analyzing feature changes in the same area over time. In this paper, we propose a large language model (LLM) augmented inference approach (SegChange-R1), which enhances the detection capability by integrating textual descriptive information and guides the model to focus on relevant change regions, accelerating convergence. We designed a linear attention-based spatial transformation module (BEV) to address modal misalignment by unifying features from different times into a BEV space. Fur","authors_text":"Fei Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-22T08:40:56Z","title":"SegChange-R1: LLM-Augmented Remote Sensing Change Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.17944","kind":"arxiv","version":2},"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":"sha256:8be8bf31f68f5c296f22cdf58457e9d7bc3a8cc4f0681f6c643c1c20a368377e","target":"record","created_at":"2026-07-05T11:28:17Z","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":"4c15318f7c1fa6abd8693674ba5272fa8c2a6da1b1eae51023bf61186a44d6dd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-22T08:40:56Z","title_canon_sha256":"7defb1678fc7035bc665a41e8d1a5c2acdd5186bc485abfca582df63068dc2b0"},"schema_version":"1.0","source":{"id":"2506.17944","kind":"arxiv","version":2}},"canonical_sha256":"2ac2daa6721732ee97a2d748afa0fe4fd1f643c4b96396d2893651d6877d0d2b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2ac2daa6721732ee97a2d748afa0fe4fd1f643c4b96396d2893651d6877d0d2b","first_computed_at":"2026-07-05T11:28:17.761643Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:28:17.761643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0jmzyYfuCW4pvcfO4rvlwnxYTA06TwI81sa1Jde9ZqgpDX1ldUny7Zby0y6v4uUqESXKpxZx0Y81UIf5N5wABA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:28:17.762124Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.17944","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8be8bf31f68f5c296f22cdf58457e9d7bc3a8cc4f0681f6c643c1c20a368377e","sha256:8951f86814c25e436b90ab50afa7390291ce49a28b87f90979a242e452b6af61"],"state_sha256":"75e5122b48a0be1bc9244dba422d5d401ae5a958d533e44e2e9521a99b3bf26c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K9w5NmR3euNlakShGx9wO/71baF3ddXZHRDWjsVFc1Y0b66eus4zvx6DInwVuqf7L6YrbtGkKhO2nbd/RIAFAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T02:34:31.710286Z","bundle_sha256":"4f99ec46a173f7f524a6d6eeab0c197abb762f5ca66791927359313cd99e6a18"}}