{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W223U2YULNLUW55CEBUH5EVEDG","short_pith_number":"pith:W223U2YU","canonical_record":{"source":{"id":"2410.18792","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-10-24T14:47:25Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"ee812a0ec0eea0a4eb90de4c067847c0d10759c246ba438e7255019c4d7d7937","abstract_canon_sha256":"dab9f9e525c15216bbb4a18e3425c632f960fe56d806d84baaaaf5618d32a6c4"},"schema_version":"1.0"},"canonical_sha256":"b6b5ba6b145b574b77a220687e92a419ab49fe842a280e61fbbd0f0aa41d367f","source":{"kind":"arxiv","id":"2410.18792","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.18792","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"arxiv_version","alias_value":"2410.18792v2","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.18792","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_12","alias_value":"W223U2YULNLU","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_16","alias_value":"W223U2YULNLUW55C","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_8","alias_value":"W223U2YU","created_at":"2026-07-05T09:25:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W223U2YULNLUW55CEBUH5EVEDG","target":"record","payload":{"canonical_record":{"source":{"id":"2410.18792","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-10-24T14:47:25Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"ee812a0ec0eea0a4eb90de4c067847c0d10759c246ba438e7255019c4d7d7937","abstract_canon_sha256":"dab9f9e525c15216bbb4a18e3425c632f960fe56d806d84baaaaf5618d32a6c4"},"schema_version":"1.0"},"canonical_sha256":"b6b5ba6b145b574b77a220687e92a419ab49fe842a280e61fbbd0f0aa41d367f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:25:49.456135Z","signature_b64":"nrvsbVdAY++SovV7UiFDfraeZdNljVl70eZY60fmTzAGgs64/etzuCecVG33elhIp7EJYhW5/BcwgQfWacUlBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6b5ba6b145b574b77a220687e92a419ab49fe842a280e61fbbd0f0aa41d367f","last_reissued_at":"2026-07-05T09:25:49.455673Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:25:49.455673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.18792","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":"2026-07-05T09:25:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A0L5C6n8cexEDYCHMji1pAQ+3dYKAGnh+Twqsm8oLJHwjORDL6aP4I9wCkk23R088KdqDI9ZAqMjQ7GPR6nNDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:18:57.204319Z"},"content_sha256":"8602f44cffc65ea34fa9ed4a51468bd50d55319de44c6ad7e94a38458a1a616c","schema_version":"1.0","event_id":"sha256:8602f44cffc65ea34fa9ed4a51468bd50d55319de44c6ad7e94a38458a1a616c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W223U2YULNLUW55CEBUH5EVEDG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An LLM Agent for Automatic Geospatial Data Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CY","authors_text":"Camille Kurtz, Sylvain Lobry, Weijie Wang, Yuxing Chen","submitted_at":"2024-10-24T14:47:25Z","abstract_excerpt":"Large language models (LLMs) are being used in data science code generation tasks, but they often struggle with complex sequential tasks, leading to logical errors. Their application to geospatial data processing is particularly challenging due to difficulties in incorporating complex data structures and spatial constraints, effectively utilizing diverse function calls, and the tendency to hallucinate less-used geospatial libraries. To tackle these problems, we introduce GeoAgent, a new interactive framework designed to help LLMs handle geospatial data processing more effectively. GeoAgent pio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.18792","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/2410.18792/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":"2026-07-05T09:25:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9lUWsNNPoXyXTL0Zghsvad7iBqyPZ/2plwY37gtC2r/UY0oD7obfMNNlg18FPQCboKjwukQM5u30KBDWZ08Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:18:57.204814Z"},"content_sha256":"0369931900f7633ea03ee48a86eb5a53a50085e9841d7eb2913995cc50c1f544","schema_version":"1.0","event_id":"sha256:0369931900f7633ea03ee48a86eb5a53a50085e9841d7eb2913995cc50c1f544"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W223U2YULNLUW55CEBUH5EVEDG/bundle.json","state_url":"https://pith.science/pith/W223U2YULNLUW55CEBUH5EVEDG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W223U2YULNLUW55CEBUH5EVEDG/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":"2026-08-09T10:18:57Z","links":{"resolver":"https://pith.science/pith/W223U2YULNLUW55CEBUH5EVEDG","bundle":"https://pith.science/pith/W223U2YULNLUW55CEBUH5EVEDG/bundle.json","state":"https://pith.science/pith/W223U2YULNLUW55CEBUH5EVEDG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W223U2YULNLUW55CEBUH5EVEDG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W223U2YULNLUW55CEBUH5EVEDG","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":"dab9f9e525c15216bbb4a18e3425c632f960fe56d806d84baaaaf5618d32a6c4","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-10-24T14:47:25Z","title_canon_sha256":"ee812a0ec0eea0a4eb90de4c067847c0d10759c246ba438e7255019c4d7d7937"},"schema_version":"1.0","source":{"id":"2410.18792","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.18792","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"arxiv_version","alias_value":"2410.18792v2","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.18792","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_12","alias_value":"W223U2YULNLU","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_16","alias_value":"W223U2YULNLUW55C","created_at":"2026-07-05T09:25:49Z"},{"alias_kind":"pith_short_8","alias_value":"W223U2YU","created_at":"2026-07-05T09:25:49Z"}],"graph_snapshots":[{"event_id":"sha256:0369931900f7633ea03ee48a86eb5a53a50085e9841d7eb2913995cc50c1f544","target":"graph","created_at":"2026-07-05T09:25:49Z","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/2410.18792/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are being used in data science code generation tasks, but they often struggle with complex sequential tasks, leading to logical errors. Their application to geospatial data processing is particularly challenging due to difficulties in incorporating complex data structures and spatial constraints, effectively utilizing diverse function calls, and the tendency to hallucinate less-used geospatial libraries. To tackle these problems, we introduce GeoAgent, a new interactive framework designed to help LLMs handle geospatial data processing more effectively. GeoAgent pio","authors_text":"Camille Kurtz, Sylvain Lobry, Weijie Wang, Yuxing Chen","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-10-24T14:47:25Z","title":"An LLM Agent for Automatic Geospatial Data Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.18792","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":"sha256:8602f44cffc65ea34fa9ed4a51468bd50d55319de44c6ad7e94a38458a1a616c","target":"record","created_at":"2026-07-05T09:25:49Z","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":"dab9f9e525c15216bbb4a18e3425c632f960fe56d806d84baaaaf5618d32a6c4","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-10-24T14:47:25Z","title_canon_sha256":"ee812a0ec0eea0a4eb90de4c067847c0d10759c246ba438e7255019c4d7d7937"},"schema_version":"1.0","source":{"id":"2410.18792","kind":"arxiv","version":2}},"canonical_sha256":"b6b5ba6b145b574b77a220687e92a419ab49fe842a280e61fbbd0f0aa41d367f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6b5ba6b145b574b77a220687e92a419ab49fe842a280e61fbbd0f0aa41d367f","first_computed_at":"2026-07-05T09:25:49.455673Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:25:49.455673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nrvsbVdAY++SovV7UiFDfraeZdNljVl70eZY60fmTzAGgs64/etzuCecVG33elhIp7EJYhW5/BcwgQfWacUlBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:25:49.456135Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.18792","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8602f44cffc65ea34fa9ed4a51468bd50d55319de44c6ad7e94a38458a1a616c","sha256:0369931900f7633ea03ee48a86eb5a53a50085e9841d7eb2913995cc50c1f544"],"state_sha256":"97e61ba88f4e709b68a5fd96f84e7cff1bc8e813296a41a8dda9061dff90bb47"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+IAcmCB/OSx7WMxE+tkMguMj5I91iGH4DdSreTLwx1GeEysYeLsdGxzS6XeQtCXo0L3CJwvu1u4xmfQONH+RCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:18:57.209841Z","bundle_sha256":"6036c980932ad6c0ca1757d1b4c53f8c3becf1d8f7f398c1145da41ae4c6ceb3"}}