{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:PEHDWG3O2ISSIUYQGUL4VBZROL","short_pith_number":"pith:PEHDWG3O","canonical_record":{"source":{"id":"2606.28049","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T12:51:22Z","cross_cats_sorted":[],"title_canon_sha256":"a31cd2e14ac76bec4825e8954161c3298b1044f0b5ccc4c33267ffd199a7f3ed","abstract_canon_sha256":"769d186f37ea1f58de50737cc72444cc821115031a3df56ecb649bf122ff980b"},"schema_version":"1.0"},"canonical_sha256":"790e3b1b6ed2252453103517ca873172cad4255cdd2199ea313f0c5dbc90774f","source":{"kind":"arxiv","id":"2606.28049","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28049","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28049v1","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28049","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_12","alias_value":"PEHDWG3O2ISS","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_16","alias_value":"PEHDWG3O2ISSIUYQ","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_8","alias_value":"PEHDWG3O","created_at":"2026-06-29T01:14:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:PEHDWG3O2ISSIUYQGUL4VBZROL","target":"record","payload":{"canonical_record":{"source":{"id":"2606.28049","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T12:51:22Z","cross_cats_sorted":[],"title_canon_sha256":"a31cd2e14ac76bec4825e8954161c3298b1044f0b5ccc4c33267ffd199a7f3ed","abstract_canon_sha256":"769d186f37ea1f58de50737cc72444cc821115031a3df56ecb649bf122ff980b"},"schema_version":"1.0"},"canonical_sha256":"790e3b1b6ed2252453103517ca873172cad4255cdd2199ea313f0c5dbc90774f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-29T01:14:56.330132Z","signature_b64":"76CZNupVcvhOJrOYRmofh5lA0OSRPAwWiBkuCxho1TELV7IbYaqu//2uHf+9cjHbd8Bf/ItEXGD0wiIz22AaCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"790e3b1b6ed2252453103517ca873172cad4255cdd2199ea313f0c5dbc90774f","last_reissued_at":"2026-06-29T01:14:56.329738Z","signature_status":"signed_v1","first_computed_at":"2026-06-29T01:14:56.329738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.28049","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":"2026-06-29T01:14:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QVA1dNZEpErHY81t22QrLlSrdbZsCptJ0MTCJbi9BQaycW5nZ0q6ZqDaB4bGEViQ1n13D1j2A34uvOEPeIQ7CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T11:27:32.123224Z"},"content_sha256":"23a5c691700a9d8b8baf7206436f7ed577bef0faa1c4abc692d2c635e3130c02","schema_version":"1.0","event_id":"sha256:23a5c691700a9d8b8baf7206436f7ed577bef0faa1c4abc692d2c635e3130c02"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:PEHDWG3O2ISSIUYQGUL4VBZROL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haotian Li, Jianwei Hu, Jinshan Lai, Keyang Wang, Leyuan Wang, Liuyu Xiang, Qiang Ma, Yida Wang, Zhaofeng He, Zonghao Guo","submitted_at":"2026-06-26T12:51:22Z","abstract_excerpt":"In recent years, multimodal large language models (MLLMs) have shown strong potential for embodied intelligence, yet their ability to maintain geometrically consistent spatial understanding across heterogeneous views remains under-evaluated. Existing benchmarks largely focus on single-agent, single-view perception, leaving a gap in the systematic assessment of collaborative air-ground settings, where multi-scale observations are complementary but introduce scale mismatch, asymmetric occlusion, and reference-frame inconsistencies. We present AirGroundBench, a diagnostic benchmark for evaluating"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28049","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/2606.28049/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":"2026-06-29T01:14:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nUfPbZ/aOYunMvFynI+nuQOlRmb3UYj+6H7zWops4dVlIZK+8lBWHwDqaojttu85wKWZc3sqrviE8hUfs2oNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T11:27:32.123618Z"},"content_sha256":"38b214c9f15e2322bc90ebc445563165af163942451d35365b8279241d72edde","schema_version":"1.0","event_id":"sha256:38b214c9f15e2322bc90ebc445563165af163942451d35365b8279241d72edde"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/bundle.json","state_url":"https://pith.science/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/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":"2026-06-30T11:27:32Z","links":{"resolver":"https://pith.science/pith/PEHDWG3O2ISSIUYQGUL4VBZROL","bundle":"https://pith.science/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/bundle.json","state":"https://pith.science/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PEHDWG3O2ISSIUYQGUL4VBZROL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PEHDWG3O2ISSIUYQGUL4VBZROL","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":"769d186f37ea1f58de50737cc72444cc821115031a3df56ecb649bf122ff980b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T12:51:22Z","title_canon_sha256":"a31cd2e14ac76bec4825e8954161c3298b1044f0b5ccc4c33267ffd199a7f3ed"},"schema_version":"1.0","source":{"id":"2606.28049","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28049","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28049v1","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28049","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_12","alias_value":"PEHDWG3O2ISS","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_16","alias_value":"PEHDWG3O2ISSIUYQ","created_at":"2026-06-29T01:14:56Z"},{"alias_kind":"pith_short_8","alias_value":"PEHDWG3O","created_at":"2026-06-29T01:14:56Z"}],"graph_snapshots":[{"event_id":"sha256:38b214c9f15e2322bc90ebc445563165af163942451d35365b8279241d72edde","target":"graph","created_at":"2026-06-29T01:14:56Z","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/2606.28049/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, multimodal large language models (MLLMs) have shown strong potential for embodied intelligence, yet their ability to maintain geometrically consistent spatial understanding across heterogeneous views remains under-evaluated. Existing benchmarks largely focus on single-agent, single-view perception, leaving a gap in the systematic assessment of collaborative air-ground settings, where multi-scale observations are complementary but introduce scale mismatch, asymmetric occlusion, and reference-frame inconsistencies. We present AirGroundBench, a diagnostic benchmark for evaluating","authors_text":"Haotian Li, Jianwei Hu, Jinshan Lai, Keyang Wang, Leyuan Wang, Liuyu Xiang, Qiang Ma, Yida Wang, Zhaofeng He, Zonghao Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T12:51:22Z","title":"AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28049","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":"sha256:23a5c691700a9d8b8baf7206436f7ed577bef0faa1c4abc692d2c635e3130c02","target":"record","created_at":"2026-06-29T01:14:56Z","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":"769d186f37ea1f58de50737cc72444cc821115031a3df56ecb649bf122ff980b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T12:51:22Z","title_canon_sha256":"a31cd2e14ac76bec4825e8954161c3298b1044f0b5ccc4c33267ffd199a7f3ed"},"schema_version":"1.0","source":{"id":"2606.28049","kind":"arxiv","version":1}},"canonical_sha256":"790e3b1b6ed2252453103517ca873172cad4255cdd2199ea313f0c5dbc90774f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"790e3b1b6ed2252453103517ca873172cad4255cdd2199ea313f0c5dbc90774f","first_computed_at":"2026-06-29T01:14:56.329738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-29T01:14:56.329738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"76CZNupVcvhOJrOYRmofh5lA0OSRPAwWiBkuCxho1TELV7IbYaqu//2uHf+9cjHbd8Bf/ItEXGD0wiIz22AaCw==","signature_status":"signed_v1","signed_at":"2026-06-29T01:14:56.330132Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.28049","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23a5c691700a9d8b8baf7206436f7ed577bef0faa1c4abc692d2c635e3130c02","sha256:38b214c9f15e2322bc90ebc445563165af163942451d35365b8279241d72edde"],"state_sha256":"324ceafab08ec644d9d308e20e43e5f44df48422e2670d6e3269871181adccba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8uQApRBtS+EEzzynabO/77TMFeGPIejMIzhk+ttzicFy3vmzo9PzujVJwXehOvGrYyVMqeJBibbyQfQM7S9lDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T11:27:32.126106Z","bundle_sha256":"b9b19054f9f271a17d8049f2a29b61ac3153313924d2067a5309d6c8df5a8603"}}