{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:P6VFFITUKTA2BVSYEYYKVFXOUK","short_pith_number":"pith:P6VFFITU","canonical_record":{"source":{"id":"1705.06979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-05-19T13:23:46Z","cross_cats_sorted":[],"title_canon_sha256":"5c151106b6608c0b9cd8e1eb1e8b3830eccffccb7320249766b0d9cca72ebc71","abstract_canon_sha256":"5124c443ff82deb62c2c8c1f6229119784d9adb75e3d546638505c825d22f8c3"},"schema_version":"1.0"},"canonical_sha256":"7faa52a27454c1a0d6582630aa96eea2a2cbc094a84b94148591f0c53a2d8a8a","source":{"kind":"arxiv","id":"1705.06979","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.06979","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"arxiv_version","alias_value":"1705.06979v2","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.06979","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"pith_short_12","alias_value":"P6VFFITUKTA2","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P6VFFITUKTA2BVSY","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P6VFFITU","created_at":"2026-05-18T12:31:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:P6VFFITUKTA2BVSYEYYKVFXOUK","target":"record","payload":{"canonical_record":{"source":{"id":"1705.06979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-05-19T13:23:46Z","cross_cats_sorted":[],"title_canon_sha256":"5c151106b6608c0b9cd8e1eb1e8b3830eccffccb7320249766b0d9cca72ebc71","abstract_canon_sha256":"5124c443ff82deb62c2c8c1f6229119784d9adb75e3d546638505c825d22f8c3"},"schema_version":"1.0"},"canonical_sha256":"7faa52a27454c1a0d6582630aa96eea2a2cbc094a84b94148591f0c53a2d8a8a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:31.833741Z","signature_b64":"vt3rgf+RYVZnmyhI3fliGH7r4nCAy2ATEC/f9l6uRRVU6sbRZnY2lWpl54MgX/7osxLaWs14aPhze+AD1zlRBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7faa52a27454c1a0d6582630aa96eea2a2cbc094a84b94148591f0c53a2d8a8a","last_reissued_at":"2026-05-18T00:18:31.833391Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:31.833391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.06979","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:18:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EFn5M/K55egRTyCtsTeT1Bsie3ZpgyjxDOhukZ9vbpqvVKeF22VO44gZcO+oy5gNCkBLcHUmDx3r1U746LAnCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T23:07:34.677267Z"},"content_sha256":"09a1df9e594d4606bbac813848c76b1fed8554021b2cc16730c4129dae5ecc4f","schema_version":"1.0","event_id":"sha256:09a1df9e594d4606bbac813848c76b1fed8554021b2cc16730c4129dae5ecc4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:P6VFFITUKTA2BVSYEYYKVFXOUK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-End Cross-Modality Retrieval with CCA Projections and Pairwise Ranking Loss","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Andreu Vall, Filip Korzeniowski, Gerhard Widmer, Jan Schl\\\"uter, Matthias Dorfer","submitted_at":"2017-05-19T13:23:46Z","abstract_excerpt":"Cross-modality retrieval encompasses retrieval tasks where the fetched items are of a different type than the search query, e.g., retrieving pictures relevant to a given text query. The state-of-the-art approach to cross-modality retrieval relies on learning a joint embedding space of the two modalities, where items from either modality are retrieved using nearest-neighbor search. In this work, we introduce a neural network layer based on Canonical Correlation Analysis (CCA) that learns better embedding spaces by analytically computing projections that maximize correlation. In contrast to prev"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.06979","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:18:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jzEVEzXMEDoB20NOmLpd7Uf5Z1Ud1GELMNcFdAl8QUspA+AJKxoiWlhq7Veimx4A6EC9zsafool5mX2YAgGsAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T23:07:34.678001Z"},"content_sha256":"7b5c84b5d52449d83e14fab2184299ba4c9e234786b45b78eeae2165752e3885","schema_version":"1.0","event_id":"sha256:7b5c84b5d52449d83e14fab2184299ba4c9e234786b45b78eeae2165752e3885"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/bundle.json","state_url":"https://pith.science/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/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":"2026-05-23T23:07:34Z","links":{"resolver":"https://pith.science/pith/P6VFFITUKTA2BVSYEYYKVFXOUK","bundle":"https://pith.science/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/bundle.json","state":"https://pith.science/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P6VFFITUKTA2BVSYEYYKVFXOUK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:P6VFFITUKTA2BVSYEYYKVFXOUK","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":"5124c443ff82deb62c2c8c1f6229119784d9adb75e3d546638505c825d22f8c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-05-19T13:23:46Z","title_canon_sha256":"5c151106b6608c0b9cd8e1eb1e8b3830eccffccb7320249766b0d9cca72ebc71"},"schema_version":"1.0","source":{"id":"1705.06979","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.06979","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"arxiv_version","alias_value":"1705.06979v2","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.06979","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"pith_short_12","alias_value":"P6VFFITUKTA2","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P6VFFITUKTA2BVSY","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P6VFFITU","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:7b5c84b5d52449d83e14fab2184299ba4c9e234786b45b78eeae2165752e3885","target":"graph","created_at":"2026-05-18T00:18:31Z","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"},"paper":{"abstract_excerpt":"Cross-modality retrieval encompasses retrieval tasks where the fetched items are of a different type than the search query, e.g., retrieving pictures relevant to a given text query. The state-of-the-art approach to cross-modality retrieval relies on learning a joint embedding space of the two modalities, where items from either modality are retrieved using nearest-neighbor search. In this work, we introduce a neural network layer based on Canonical Correlation Analysis (CCA) that learns better embedding spaces by analytically computing projections that maximize correlation. In contrast to prev","authors_text":"Andreu Vall, Filip Korzeniowski, Gerhard Widmer, Jan Schl\\\"uter, Matthias Dorfer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-05-19T13:23:46Z","title":"End-to-End Cross-Modality Retrieval with CCA Projections and Pairwise Ranking Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.06979","kind":"arxiv","version":2},"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":"sha256:09a1df9e594d4606bbac813848c76b1fed8554021b2cc16730c4129dae5ecc4f","target":"record","created_at":"2026-05-18T00:18:31Z","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":"5124c443ff82deb62c2c8c1f6229119784d9adb75e3d546638505c825d22f8c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-05-19T13:23:46Z","title_canon_sha256":"5c151106b6608c0b9cd8e1eb1e8b3830eccffccb7320249766b0d9cca72ebc71"},"schema_version":"1.0","source":{"id":"1705.06979","kind":"arxiv","version":2}},"canonical_sha256":"7faa52a27454c1a0d6582630aa96eea2a2cbc094a84b94148591f0c53a2d8a8a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7faa52a27454c1a0d6582630aa96eea2a2cbc094a84b94148591f0c53a2d8a8a","first_computed_at":"2026-05-18T00:18:31.833391Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:31.833391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vt3rgf+RYVZnmyhI3fliGH7r4nCAy2ATEC/f9l6uRRVU6sbRZnY2lWpl54MgX/7osxLaWs14aPhze+AD1zlRBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:31.833741Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.06979","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:09a1df9e594d4606bbac813848c76b1fed8554021b2cc16730c4129dae5ecc4f","sha256:7b5c84b5d52449d83e14fab2184299ba4c9e234786b45b78eeae2165752e3885"],"state_sha256":"00b09584137bfdd59e6ae2f5c334dc993e4609ebab42830092637304a49bbe32"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P77GJSqBv1CXZ731ww2G1yYWkKwAzAzud9GeBMP8ru6yAw7h035HZYZkCL7QzG+CGTQ9xZPEZG6c/y8fWezqCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T23:07:34.681200Z","bundle_sha256":"56f541d9bca059f0cdda00d84efe7f22818eb160323f2b135313b4e591c23007"}}