{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:AS6CF4ZOGR4ZXIBAAZDJBLLHUF","short_pith_number":"pith:AS6CF4ZO","canonical_record":{"source":{"id":"2606.23892","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T19:41:57Z","cross_cats_sorted":[],"title_canon_sha256":"ce2eebb00e13b17f4ab2b8b03407484b76f0a781c5b32c6443c502981984cf52","abstract_canon_sha256":"94a0d9aa0dc2c40c49c3fa38d765d6a812cac13eccd1ae3091c32aba6ffe6081"},"schema_version":"1.0"},"canonical_sha256":"04bc22f32e34799ba020064690ad67a1542d5667e337cb632e6295fffc2ed032","source":{"kind":"arxiv","id":"2606.23892","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23892","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23892v1","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23892","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_12","alias_value":"AS6CF4ZOGR4Z","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_16","alias_value":"AS6CF4ZOGR4ZXIBA","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_8","alias_value":"AS6CF4ZO","created_at":"2026-06-24T00:14:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:AS6CF4ZOGR4ZXIBAAZDJBLLHUF","target":"record","payload":{"canonical_record":{"source":{"id":"2606.23892","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T19:41:57Z","cross_cats_sorted":[],"title_canon_sha256":"ce2eebb00e13b17f4ab2b8b03407484b76f0a781c5b32c6443c502981984cf52","abstract_canon_sha256":"94a0d9aa0dc2c40c49c3fa38d765d6a812cac13eccd1ae3091c32aba6ffe6081"},"schema_version":"1.0"},"canonical_sha256":"04bc22f32e34799ba020064690ad67a1542d5667e337cb632e6295fffc2ed032","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-24T00:14:29.514231Z","signature_b64":"XmxBryjm3+ImotExlEESO5IZPnYLoV/HNxWbUwmkRHvL1yKi1SROnP3CFa1+o7S05n/12Gl5G7Br7Okk8CleBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04bc22f32e34799ba020064690ad67a1542d5667e337cb632e6295fffc2ed032","last_reissued_at":"2026-06-24T00:14:29.513824Z","signature_status":"signed_v1","first_computed_at":"2026-06-24T00:14:29.513824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.23892","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":"2026-06-24T00:14:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2FKBqX21Fhb3cJlpK/EujKalp2T+ztOFXhJrHroXTHLx1ZBtJ/hv3qcsjpJ9QYy4BKDYS7L/qYel3h+Tp60bAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T20:13:00.975633Z"},"content_sha256":"49803acf6403763bfe6150b6c681a156a4c5b18882b8aef15b85c3663867b2c6","schema_version":"1.0","event_id":"sha256:49803acf6403763bfe6150b6c681a156a4c5b18882b8aef15b85c3663867b2c6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:AS6CF4ZOGR4ZXIBAAZDJBLLHUF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mengxin Zheng, Qian Lou, Yifei Zhao","submitted_at":"2026-06-22T19:41:57Z","abstract_excerpt":"Vision-language models (VLMs) are increasingly used as perception-reasoning backbones for embodied intelligence in safety-critical physical systems, where perception or reasoning errors can lead to unsafe decisions or actions. Although many red-teaming methods have been developed to probe VLM vulnerabilities, their evaluation remains fragmented across datasets, metrics, and threat models, making direct comparison difficult and obscuring whether observed differences arise from stronger attacks, more vulnerable models, or incompatible evaluation settings. Existing chatbot-centric red-teaming ben"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23892","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/2606.23892/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":"2026-06-24T00:14:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nVFGZSZv2lyK4r3atjUgKowqPhiFAhKT7NlInExpSmQg89FDPbjU64GQ3q0ahnvIkHtTTrTldqXxcWoc26J1Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T20:13:00.976020Z"},"content_sha256":"391f3fe5ceca3505874ac7029d66dd31bb6e0aff1ec0d13e09315527accffb29","schema_version":"1.0","event_id":"sha256:391f3fe5ceca3505874ac7029d66dd31bb6e0aff1ec0d13e09315527accffb29"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/bundle.json","state_url":"https://pith.science/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/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":"2026-06-27T20:13:00Z","links":{"resolver":"https://pith.science/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF","bundle":"https://pith.science/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/bundle.json","state":"https://pith.science/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AS6CF4ZOGR4ZXIBAAZDJBLLHUF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:AS6CF4ZOGR4ZXIBAAZDJBLLHUF","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":"94a0d9aa0dc2c40c49c3fa38d765d6a812cac13eccd1ae3091c32aba6ffe6081","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T19:41:57Z","title_canon_sha256":"ce2eebb00e13b17f4ab2b8b03407484b76f0a781c5b32c6443c502981984cf52"},"schema_version":"1.0","source":{"id":"2606.23892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23892","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23892v1","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23892","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_12","alias_value":"AS6CF4ZOGR4Z","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_16","alias_value":"AS6CF4ZOGR4ZXIBA","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_8","alias_value":"AS6CF4ZO","created_at":"2026-06-24T00:14:29Z"}],"graph_snapshots":[{"event_id":"sha256:391f3fe5ceca3505874ac7029d66dd31bb6e0aff1ec0d13e09315527accffb29","target":"graph","created_at":"2026-06-24T00:14:29Z","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/2606.23892/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language models (VLMs) are increasingly used as perception-reasoning backbones for embodied intelligence in safety-critical physical systems, where perception or reasoning errors can lead to unsafe decisions or actions. Although many red-teaming methods have been developed to probe VLM vulnerabilities, their evaluation remains fragmented across datasets, metrics, and threat models, making direct comparison difficult and obscuring whether observed differences arise from stronger attacks, more vulnerable models, or incompatible evaluation settings. Existing chatbot-centric red-teaming ben","authors_text":"Mengxin Zheng, Qian Lou, Yifei Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T19:41:57Z","title":"REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23892","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":"sha256:49803acf6403763bfe6150b6c681a156a4c5b18882b8aef15b85c3663867b2c6","target":"record","created_at":"2026-06-24T00:14:29Z","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":"94a0d9aa0dc2c40c49c3fa38d765d6a812cac13eccd1ae3091c32aba6ffe6081","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T19:41:57Z","title_canon_sha256":"ce2eebb00e13b17f4ab2b8b03407484b76f0a781c5b32c6443c502981984cf52"},"schema_version":"1.0","source":{"id":"2606.23892","kind":"arxiv","version":1}},"canonical_sha256":"04bc22f32e34799ba020064690ad67a1542d5667e337cb632e6295fffc2ed032","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04bc22f32e34799ba020064690ad67a1542d5667e337cb632e6295fffc2ed032","first_computed_at":"2026-06-24T00:14:29.513824Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T00:14:29.513824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XmxBryjm3+ImotExlEESO5IZPnYLoV/HNxWbUwmkRHvL1yKi1SROnP3CFa1+o7S05n/12Gl5G7Br7Okk8CleBQ==","signature_status":"signed_v1","signed_at":"2026-06-24T00:14:29.514231Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:49803acf6403763bfe6150b6c681a156a4c5b18882b8aef15b85c3663867b2c6","sha256:391f3fe5ceca3505874ac7029d66dd31bb6e0aff1ec0d13e09315527accffb29"],"state_sha256":"6ec489a47a39ac8be583a7fa736bd94cc7a5d21543a1fdd75e72a33fb834ef4a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sG/0sv9Ft2/3ahKUs0iywwik1LRdwhCAV+CWFHB2+8euOyGJvUHWrv1ZcegE3P83zIo87C8kcqGAV3IGMn28AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T20:13:00.977968Z","bundle_sha256":"8b64125e9351eb59cbc1fcd2c2835b782c75b5b906cfae3473324b614bdf9c26"}}