{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:J6MW3NRBU2ICXZR3ABRIASXHWE","short_pith_number":"pith:J6MW3NRB","canonical_record":{"source":{"id":"2608.06948","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-07T08:25:14Z","cross_cats_sorted":[],"title_canon_sha256":"215fbba0898ffba52db5458d2d342d6519ac67a1cae6da40d8d6588193ad5aee","abstract_canon_sha256":"f96ea79f70960693b4ca6b9e6083f16c08a23c920549f53ad7fb170351aaaebd"},"schema_version":"1.0"},"canonical_sha256":"4f996db621a6902be63b0062804ae7b13188c6335b6f4fe1354159dd74271e41","source":{"kind":"arxiv","id":"2608.06948","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06948","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06948v1","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06948","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_12","alias_value":"J6MW3NRBU2IC","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_16","alias_value":"J6MW3NRBU2ICXZR3","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_8","alias_value":"J6MW3NRB","created_at":"2026-08-10T01:12:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:J6MW3NRBU2ICXZR3ABRIASXHWE","target":"record","payload":{"canonical_record":{"source":{"id":"2608.06948","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-07T08:25:14Z","cross_cats_sorted":[],"title_canon_sha256":"215fbba0898ffba52db5458d2d342d6519ac67a1cae6da40d8d6588193ad5aee","abstract_canon_sha256":"f96ea79f70960693b4ca6b9e6083f16c08a23c920549f53ad7fb170351aaaebd"},"schema_version":"1.0"},"canonical_sha256":"4f996db621a6902be63b0062804ae7b13188c6335b6f4fe1354159dd74271e41","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-10T01:12:37.045161Z","signature_b64":"law81aAsCHl940SI7w4R0BEXkZw8b0xVDPUdvSGLEClUWeFd6oXIHk2eCh1assMOi37iwCPmECsZgny1fxUPAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f996db621a6902be63b0062804ae7b13188c6335b6f4fe1354159dd74271e41","last_reissued_at":"2026-08-10T01:12:37.041853Z","signature_status":"signed_v1","first_computed_at":"2026-08-10T01:12:37.041853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.06948","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":"2026-08-10T01:12:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3BqbJ0/SZ9uMACbybg8pimOYJSTVYozRtpiMcZYEccZx65fnVc7MPKzj54v/OcAd3hYzV7q6EpR3nFtL6vpKAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T07:34:40.072977Z"},"content_sha256":"b7e221366b57bedd46e9bbfc5ae4ba342650f39bcfc571f74eb9902c5b36b6ee","schema_version":"1.0","event_id":"sha256:b7e221366b57bedd46e9bbfc5ae4ba342650f39bcfc571f74eb9902c5b36b6ee"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:J6MW3NRBU2ICXZR3ABRIASXHWE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LMM Modality Transfer: A Pre-requisite for Autonomous GIS Agents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Alexandra Fortacz-Lazan, Franziska H\\\"ubl, Ivan Majic, Krzysztof Janowicz, Meilin Shi, Mina Karimi, Zexian Huang, Zilong Liu","submitted_at":"2026-08-07T08:25:14Z","abstract_excerpt":"AI models are becoming increasingly adept at understanding and processing spatial information, thereby facilitating agentic problem-solving in spatial tasks and workflows. However, most of the research on their spatial capabilities (e.g., spatial reasoning) has focused on the textual modality as input and output. This contrasts with the human approach to GIS workflows, where text and visual modalities are often used together, interchangeably, and in a complementary manner. Thus, to truly achieve an automated GIS analysis pipeline or carry out human-designed GIS workflows, AI models --- Large M"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06948","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/2608.06948/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":"2026-08-10T01:12:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WCi/ZCsebhl5uARnT/Kk6BcKbgPMdlOifFgk5dxrWxiutPsdDaFvwF/HdwSeuenwi2epaqDr9UhcNhiCMxUeBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T07:34:40.073528Z"},"content_sha256":"a0409ae50dae98f29e214d2becba4c586502b9f648f313799fa735ecbfd8e2e3","schema_version":"1.0","event_id":"sha256:a0409ae50dae98f29e214d2becba4c586502b9f648f313799fa735ecbfd8e2e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/bundle.json","state_url":"https://pith.science/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/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":"2026-08-11T07:34:40Z","links":{"resolver":"https://pith.science/pith/J6MW3NRBU2ICXZR3ABRIASXHWE","bundle":"https://pith.science/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/bundle.json","state":"https://pith.science/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J6MW3NRBU2ICXZR3ABRIASXHWE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:J6MW3NRBU2ICXZR3ABRIASXHWE","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":"f96ea79f70960693b4ca6b9e6083f16c08a23c920549f53ad7fb170351aaaebd","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-07T08:25:14Z","title_canon_sha256":"215fbba0898ffba52db5458d2d342d6519ac67a1cae6da40d8d6588193ad5aee"},"schema_version":"1.0","source":{"id":"2608.06948","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06948","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06948v1","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06948","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_12","alias_value":"J6MW3NRBU2IC","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_16","alias_value":"J6MW3NRBU2ICXZR3","created_at":"2026-08-10T01:12:37Z"},{"alias_kind":"pith_short_8","alias_value":"J6MW3NRB","created_at":"2026-08-10T01:12:37Z"}],"graph_snapshots":[{"event_id":"sha256:a0409ae50dae98f29e214d2becba4c586502b9f648f313799fa735ecbfd8e2e3","target":"graph","created_at":"2026-08-10T01:12:37Z","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/2608.06948/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"AI models are becoming increasingly adept at understanding and processing spatial information, thereby facilitating agentic problem-solving in spatial tasks and workflows. However, most of the research on their spatial capabilities (e.g., spatial reasoning) has focused on the textual modality as input and output. This contrasts with the human approach to GIS workflows, where text and visual modalities are often used together, interchangeably, and in a complementary manner. Thus, to truly achieve an automated GIS analysis pipeline or carry out human-designed GIS workflows, AI models --- Large M","authors_text":"Alexandra Fortacz-Lazan, Franziska H\\\"ubl, Ivan Majic, Krzysztof Janowicz, Meilin Shi, Mina Karimi, Zexian Huang, Zilong Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-07T08:25:14Z","title":"LMM Modality Transfer: A Pre-requisite for Autonomous GIS Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06948","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:b7e221366b57bedd46e9bbfc5ae4ba342650f39bcfc571f74eb9902c5b36b6ee","target":"record","created_at":"2026-08-10T01:12:37Z","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":"f96ea79f70960693b4ca6b9e6083f16c08a23c920549f53ad7fb170351aaaebd","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-07T08:25:14Z","title_canon_sha256":"215fbba0898ffba52db5458d2d342d6519ac67a1cae6da40d8d6588193ad5aee"},"schema_version":"1.0","source":{"id":"2608.06948","kind":"arxiv","version":1}},"canonical_sha256":"4f996db621a6902be63b0062804ae7b13188c6335b6f4fe1354159dd74271e41","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4f996db621a6902be63b0062804ae7b13188c6335b6f4fe1354159dd74271e41","first_computed_at":"2026-08-10T01:12:37.041853Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-10T01:12:37.041853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"law81aAsCHl940SI7w4R0BEXkZw8b0xVDPUdvSGLEClUWeFd6oXIHk2eCh1assMOi37iwCPmECsZgny1fxUPAg==","signature_status":"signed_v1","signed_at":"2026-08-10T01:12:37.045161Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.06948","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7e221366b57bedd46e9bbfc5ae4ba342650f39bcfc571f74eb9902c5b36b6ee","sha256:a0409ae50dae98f29e214d2becba4c586502b9f648f313799fa735ecbfd8e2e3"],"state_sha256":"a85c87835d3bf2dd10c82d18c3d1a8944a762ee6afc462a39f87ddbbe748d83c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cfNxFpEshKBR/aeDXtq83wImQ3NW1Kznz5UCqfthCMpFgZ+lCU3tBO6RJlaTAhydSlo96jjWlfaqeuz2yHODAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T07:34:40.078002Z","bundle_sha256":"d057a3f52a11b0cdb37ab9a13d6f76618cc36586ffd749a716c4ab85cafe8371"}}