{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SZUCTM3MC5NJO23KSGAADJFBVV","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":"8650ef9a581bbd8af40f814f27cef543a8f7e292be364093c6dd5faef98380ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T09:01:10Z","title_canon_sha256":"5a8af626cfb430f7147bfafd597ac58886eaabc8a4bf2c5d5e5676e1cea732ad"},"schema_version":"1.0","source":{"id":"2501.18618","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18618","created_at":"2026-07-05T11:20:50Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18618v1","created_at":"2026-07-05T11:20:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18618","created_at":"2026-07-05T11:20:50Z"},{"alias_kind":"pith_short_12","alias_value":"SZUCTM3MC5NJ","created_at":"2026-07-05T11:20:50Z"},{"alias_kind":"pith_short_16","alias_value":"SZUCTM3MC5NJO23K","created_at":"2026-07-05T11:20:50Z"},{"alias_kind":"pith_short_8","alias_value":"SZUCTM3M","created_at":"2026-07-05T11:20:50Z"}],"graph_snapshots":[{"event_id":"sha256:053abcaa30fbac3263d92e3330e30a53073c8c3485ed8255230e3fa7f01dad7e","target":"graph","created_at":"2026-07-05T11:20:50Z","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/2501.18618/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The communication scenarios and channel characteristics of 6G will be more complex and difficult to characterize. Conventional methods for channel prediction face challenges in achieving an optimal balance between accuracy, practicality, and generalizability. Additionally, they often fail to effectively leverage environmental features. Within the framework of integration communication and artificial intelligence as a pivotal development vision for 6G, it is imperative to achieve intelligent prediction of channel characteristics. Vision-aided methods have been employed in various wireless commu","authors_text":"Bo Ai, Mi Yang, Ruisi He, Xuejian Zhang, Zhengyu Zhang, Ziyi Qi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T09:01:10Z","title":"Vision Aided Channel Prediction for Vehicular Communications: A Case Study of Received Power Prediction Using RGB Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18618","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:f463aa0e5ec07b02082597d1f38986a0318f52acd6aefac6c1faec25c91dd00e","target":"record","created_at":"2026-07-05T11:20:50Z","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":"8650ef9a581bbd8af40f814f27cef543a8f7e292be364093c6dd5faef98380ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T09:01:10Z","title_canon_sha256":"5a8af626cfb430f7147bfafd597ac58886eaabc8a4bf2c5d5e5676e1cea732ad"},"schema_version":"1.0","source":{"id":"2501.18618","kind":"arxiv","version":1}},"canonical_sha256":"966829b36c175a976b6a918001a4a1ad5c3357be479083e748616f43776cd0ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"966829b36c175a976b6a918001a4a1ad5c3357be479083e748616f43776cd0ba","first_computed_at":"2026-07-05T11:20:50.113885Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:50.113885Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+XmA1Wf3OgI872MSnyXb/9xpV6mIpVhDJTOgxjT0+hWMpH7uP5/RGQzW9zlkU/Mv6x9XurKmuOdGHJ1XtaQoDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:50.114376Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.18618","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f463aa0e5ec07b02082597d1f38986a0318f52acd6aefac6c1faec25c91dd00e","sha256:053abcaa30fbac3263d92e3330e30a53073c8c3485ed8255230e3fa7f01dad7e"],"state_sha256":"c4141fe891ad101eeb2857ae8816575208f3c6845573d89bd186318cbc1e5c37"}