{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LSTAIVTR4L4YESSTFNYENBCMZF","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":"7a4ca81de03fc41b685cb0c8ba741b5d08ead99a470e7d8840a156faf6472409","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T07:08:14Z","title_canon_sha256":"67bb33424cc23640a89edf76cf44fc0ab00c5944ece8e10f6c1b4e16374b4e48"},"schema_version":"1.0","source":{"id":"2412.17339","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17339","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17339v1","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17339","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_12","alias_value":"LSTAIVTR4L4Y","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_16","alias_value":"LSTAIVTR4L4YESST","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_8","alias_value":"LSTAIVTR","created_at":"2026-07-05T09:53:21Z"}],"graph_snapshots":[{"event_id":"sha256:6f6117b9b7e6bfb46af5a7ea3a4e20fc7246dd20c4a88f4f05d0faa0be8fc9c0","target":"graph","created_at":"2026-07-05T09:53:21Z","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/2412.17339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Remote-sensing mineral exploration is critical for identifying economically viable mineral deposits, yet it poses significant challenges for multimodal large language models (MLLMs). These include limitations in domain-specific geological knowledge and difficulties in reasoning across multiple remote-sensing images, further exacerbating long-context issues. To address these, we present MineAgent, a modular framework leveraging hierarchical judging and decision-making modules to improve multi-image reasoning and spatial-spectral integration. Complementing this, we propose MineBench, a benchmark","authors_text":"Beibei Yu, Denqi Li, Hongbin Na, Ling Chen, Tao Shen","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T07:08:14Z","title":"MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17339","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":"sha256:0d43fad6ea7b8c340d499755fe36e2e4c58d2f4bd0546f165397e04879a39e03","target":"record","created_at":"2026-07-05T09:53:21Z","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":"7a4ca81de03fc41b685cb0c8ba741b5d08ead99a470e7d8840a156faf6472409","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T07:08:14Z","title_canon_sha256":"67bb33424cc23640a89edf76cf44fc0ab00c5944ece8e10f6c1b4e16374b4e48"},"schema_version":"1.0","source":{"id":"2412.17339","kind":"arxiv","version":1}},"canonical_sha256":"5ca6045671e2f9824a532b7046844cc95e2061ba8b9a214f48c44dc94416e42f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ca6045671e2f9824a532b7046844cc95e2061ba8b9a214f48c44dc94416e42f","first_computed_at":"2026-07-05T09:53:21.045071Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:53:21.045071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"21zW89w5UyIgk5xitmEJ9Bz+RwdsHx5176+EGCOngkaqRPStDfkgN7iZGlN8j6VbPCtMtJ9lwFm9uab2HhRrAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:53:21.045496Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.17339","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0d43fad6ea7b8c340d499755fe36e2e4c58d2f4bd0546f165397e04879a39e03","sha256:6f6117b9b7e6bfb46af5a7ea3a4e20fc7246dd20c4a88f4f05d0faa0be8fc9c0"],"state_sha256":"3ce93209e032d8e099bc56fbda77f90ce2c1c77741ad5d2743c3b3946617d180"}