{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:EKXTSEJZZCKNPWLWDM6E7PFU5T","short_pith_number":"pith:EKXTSEJZ","canonical_record":{"source":{"id":"2505.11216","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T13:12:41Z","cross_cats_sorted":[],"title_canon_sha256":"66221ec0fd41cd1e8d42b696b475395aa2fac40fec56ab6981c150a346d13faf","abstract_canon_sha256":"b9e0137192895d46a53d114d77c1f791f85e6c8f9f051b2e51e039335ccd9cb2"},"schema_version":"1.0"},"canonical_sha256":"22af391139c894d7d9761b3c4fbcb4ece6fd311731b339101690c5767b52e590","source":{"kind":"arxiv","id":"2505.11216","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11216","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11216v1","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11216","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"EKXTSEJZZCKN","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"EKXTSEJZZCKNPWLW","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"EKXTSEJZ","created_at":"2026-07-05T11:04:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:EKXTSEJZZCKNPWLWDM6E7PFU5T","target":"record","payload":{"canonical_record":{"source":{"id":"2505.11216","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T13:12:41Z","cross_cats_sorted":[],"title_canon_sha256":"66221ec0fd41cd1e8d42b696b475395aa2fac40fec56ab6981c150a346d13faf","abstract_canon_sha256":"b9e0137192895d46a53d114d77c1f791f85e6c8f9f051b2e51e039335ccd9cb2"},"schema_version":"1.0"},"canonical_sha256":"22af391139c894d7d9761b3c4fbcb4ece6fd311731b339101690c5767b52e590","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:04:12.914222Z","signature_b64":"HUg2hHoEwr0SAoJIFE8cpV1W9bjsVtRX+icESuPFrnbOTBeQeYQ/FnRQB7tFraSPit9m8r6jJFhZmek/rmdTDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22af391139c894d7d9761b3c4fbcb4ece6fd311731b339101690c5767b52e590","last_reissued_at":"2026-07-05T11:04:12.913720Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:04:12.913720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.11216","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":"2026-07-05T11:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZaOGsUb+i8WELSkMbBpyp/ytPkTAzrHNE1b38zskU0WkpLm4zORztXuB5tGPJ+x3E/f5v4UDQ/hBYpbMWCceCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:09:08.949960Z"},"content_sha256":"24652e26d463fa52f298eaa5b2870d6ce1206824f2fed632423517e2207be918","schema_version":"1.0","event_id":"sha256:24652e26d463fa52f298eaa5b2870d6ce1206824f2fed632423517e2207be918"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:EKXTSEJZZCKNPWLWDM6E7PFU5T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GeoMM: On Geodesic Perspective for Multi-modal Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingbing Ni, Hang Wang, Shibin Mei","submitted_at":"2025-05-16T13:12:41Z","abstract_excerpt":"Geodesic distance serves as a reliable means of measuring distance in nonlinear spaces, and such nonlinear manifolds are prevalent in the current multimodal learning. In these scenarios, some samples may exhibit high similarity, yet they convey different semantics, making traditional distance metrics inadequate for distinguishing between positive and negative samples. This paper introduces geodesic distance as a novel distance metric in multi-modal learning for the first time, to mine correlations between samples, aiming to address the limitations of common distance metric. Our approach incorp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11216","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/2505.11216/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":"2026-07-05T11:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FcLlgZusxmKKFybd4YTu+SySshZOyYcQFXL621Q9VxRsbz8R1H4tnYrIr3Uvy/1WwnOqhKNyjZPU3RHRFAuSAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:09:08.950881Z"},"content_sha256":"a6d81deaa3dd2f32e29b02aa4639c882138bdc29a0de59f42f46cec621d77269","schema_version":"1.0","event_id":"sha256:a6d81deaa3dd2f32e29b02aa4639c882138bdc29a0de59f42f46cec621d77269"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/bundle.json","state_url":"https://pith.science/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/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":"2026-08-16T04:09:08Z","links":{"resolver":"https://pith.science/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T","bundle":"https://pith.science/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/bundle.json","state":"https://pith.science/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EKXTSEJZZCKNPWLWDM6E7PFU5T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EKXTSEJZZCKNPWLWDM6E7PFU5T","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":"b9e0137192895d46a53d114d77c1f791f85e6c8f9f051b2e51e039335ccd9cb2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T13:12:41Z","title_canon_sha256":"66221ec0fd41cd1e8d42b696b475395aa2fac40fec56ab6981c150a346d13faf"},"schema_version":"1.0","source":{"id":"2505.11216","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11216","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11216v1","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11216","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"EKXTSEJZZCKN","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"EKXTSEJZZCKNPWLW","created_at":"2026-07-05T11:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"EKXTSEJZ","created_at":"2026-07-05T11:04:12Z"}],"graph_snapshots":[{"event_id":"sha256:a6d81deaa3dd2f32e29b02aa4639c882138bdc29a0de59f42f46cec621d77269","target":"graph","created_at":"2026-07-05T11:04:12Z","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/2505.11216/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Geodesic distance serves as a reliable means of measuring distance in nonlinear spaces, and such nonlinear manifolds are prevalent in the current multimodal learning. In these scenarios, some samples may exhibit high similarity, yet they convey different semantics, making traditional distance metrics inadequate for distinguishing between positive and negative samples. This paper introduces geodesic distance as a novel distance metric in multi-modal learning for the first time, to mine correlations between samples, aiming to address the limitations of common distance metric. Our approach incorp","authors_text":"Bingbing Ni, Hang Wang, Shibin Mei","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T13:12:41Z","title":"GeoMM: On Geodesic Perspective for Multi-modal Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11216","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":"sha256:24652e26d463fa52f298eaa5b2870d6ce1206824f2fed632423517e2207be918","target":"record","created_at":"2026-07-05T11:04:12Z","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":"b9e0137192895d46a53d114d77c1f791f85e6c8f9f051b2e51e039335ccd9cb2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T13:12:41Z","title_canon_sha256":"66221ec0fd41cd1e8d42b696b475395aa2fac40fec56ab6981c150a346d13faf"},"schema_version":"1.0","source":{"id":"2505.11216","kind":"arxiv","version":1}},"canonical_sha256":"22af391139c894d7d9761b3c4fbcb4ece6fd311731b339101690c5767b52e590","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22af391139c894d7d9761b3c4fbcb4ece6fd311731b339101690c5767b52e590","first_computed_at":"2026-07-05T11:04:12.913720Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:12.913720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HUg2hHoEwr0SAoJIFE8cpV1W9bjsVtRX+icESuPFrnbOTBeQeYQ/FnRQB7tFraSPit9m8r6jJFhZmek/rmdTDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:12.914222Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11216","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24652e26d463fa52f298eaa5b2870d6ce1206824f2fed632423517e2207be918","sha256:a6d81deaa3dd2f32e29b02aa4639c882138bdc29a0de59f42f46cec621d77269"],"state_sha256":"2136cdc90cb690c53d1efff4e29c2074e264587163302ec07caaf6ffea6d42f7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3UNVxWRxqJXf70rSErDS8Cy4Z6NPjIbrAHbSSz/sj7oXWLuEaUYKLGqRA/GOQItGiIIJmHxGQI0JjJTN4m7hDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T04:09:08.956102Z","bundle_sha256":"f6f009f3d7d09b476dd5028eda51fea9f5c7cb59b6306104f543f5fa7a25084e"}}