{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:R73RVP7PJKWSDKEAADA3ZGAEGC","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":"7b36fe210f739a83e4f4e7f0172309e330af5bcd06719acd46a2046302bb7d8d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T20:37:24Z","title_canon_sha256":"08ce65c982744de11abfde378d37afd03af66472b28d3ed8d921c52681fe19c3"},"schema_version":"1.0","source":{"id":"2405.00709","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.00709","created_at":"2026-07-05T08:14:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.00709v1","created_at":"2026-07-05T08:14:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.00709","created_at":"2026-07-05T08:14:25Z"},{"alias_kind":"pith_short_12","alias_value":"R73RVP7PJKWS","created_at":"2026-07-05T08:14:25Z"},{"alias_kind":"pith_short_16","alias_value":"R73RVP7PJKWSDKEA","created_at":"2026-07-05T08:14:25Z"},{"alias_kind":"pith_short_8","alias_value":"R73RVP7P","created_at":"2026-07-05T08:14:25Z"}],"graph_snapshots":[{"event_id":"sha256:d4a7143f77c2af57a33d25fdf2ca8d730a8bd41d502f3675a49b7ac1429542fe","target":"graph","created_at":"2026-07-05T08:14:25Z","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/2405.00709/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Tool-augmented Large Language Models (LLMs) have shown impressive capabilities in remote sensing (RS) applications. However, existing benchmarks assume question-answering input templates over predefined image-text data pairs. These standalone instructions neglect the intricacies of realistic user-grounded tasks. Consider a geospatial analyst: they zoom in a map area, they draw a region over which to collect satellite imagery, and they succinctly ask \"Detect all objects here\". Where is `here`, if it is not explicitly hardcoded in the image-text template, but instead is implied by the system sta","authors_text":"Dimitrios Stamoulis, Michael Fore, Simranjit Singh","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T20:37:24Z","title":"Evaluating Tool-Augmented Agents in Remote Sensing Platforms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.00709","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:e24feeef84acdb9567b48baab0012a45df8f47a6871a47ebb584c00836db482f","target":"record","created_at":"2026-07-05T08:14:25Z","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":"7b36fe210f739a83e4f4e7f0172309e330af5bcd06719acd46a2046302bb7d8d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T20:37:24Z","title_canon_sha256":"08ce65c982744de11abfde378d37afd03af66472b28d3ed8d921c52681fe19c3"},"schema_version":"1.0","source":{"id":"2405.00709","kind":"arxiv","version":1}},"canonical_sha256":"8ff71abfef4aad21a88000c1bc980430865e77c571dd0035149a0320be45f588","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8ff71abfef4aad21a88000c1bc980430865e77c571dd0035149a0320be45f588","first_computed_at":"2026-07-05T08:14:25.175865Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:14:25.175865Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lb6g8Vm3kVKdcN1KIjPObW7BPyqwUqlwiXIdVZziZ11p8GOHM0ZT3egRfkVPJC3nKxRY5W2wCGeHsadS6xuSBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:14:25.176296Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.00709","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e24feeef84acdb9567b48baab0012a45df8f47a6871a47ebb584c00836db482f","sha256:d4a7143f77c2af57a33d25fdf2ca8d730a8bd41d502f3675a49b7ac1429542fe"],"state_sha256":"cbdd6ea01d745ecc0d7504d875df0950793ea201112ea8e05059b5b4534609b5"}