{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:BXRGWKNJHTMDXHPK5J3Y56TJMG","short_pith_number":"pith:BXRGWKNJ","canonical_record":{"source":{"id":"1707.09074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-27T23:30:53Z","cross_cats_sorted":[],"title_canon_sha256":"b94f2cd5165c8bef76acaa4732bd61c2ecaec17c2290e0ba5391957907d5a296","abstract_canon_sha256":"ee7c046d1dca564358cca6fc5a9ca961b0498bcf0a2d99d75e0436e260a0ed29"},"schema_version":"1.0"},"canonical_sha256":"0de26b29a93cd83b9deaea778efa69618927fca0be323358c1f4088457558088","source":{"kind":"arxiv","id":"1707.09074","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.09074","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"arxiv_version","alias_value":"1707.09074v1","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.09074","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"pith_short_12","alias_value":"BXRGWKNJHTMD","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BXRGWKNJHTMDXHPK","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BXRGWKNJ","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:BXRGWKNJHTMDXHPK5J3Y56TJMG","target":"record","payload":{"canonical_record":{"source":{"id":"1707.09074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-27T23:30:53Z","cross_cats_sorted":[],"title_canon_sha256":"b94f2cd5165c8bef76acaa4732bd61c2ecaec17c2290e0ba5391957907d5a296","abstract_canon_sha256":"ee7c046d1dca564358cca6fc5a9ca961b0498bcf0a2d99d75e0436e260a0ed29"},"schema_version":"1.0"},"canonical_sha256":"0de26b29a93cd83b9deaea778efa69618927fca0be323358c1f4088457558088","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:17.184707Z","signature_b64":"WuZCE5jzAXuWfuQR5cEhlfqssm1OAXove+G9zvQrPZifhbxsrUHTPaDNWJ2vvYnR0acGx5lfCBOMPw6wSov2Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0de26b29a93cd83b9deaea778efa69618927fca0be323358c1f4088457558088","last_reissued_at":"2026-05-18T00:39:17.183987Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:17.183987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.09074","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":"2026-05-18T00:39:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OmC/i1ZbhGAwQu3lw0xh5PrbVSUcqTH9vtKHFN32E3BAFHfTegkGfzAPq1G2ynqZq6pJUkaZQMIQ51Ci1KUvAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T04:03:58.332634Z"},"content_sha256":"54888a82ab90c574d7aa7a433deea26c026ddd8638d54b6e565fbde01f6299e9","schema_version":"1.0","event_id":"sha256:54888a82ab90c574d7aa7a433deea26c026ddd8638d54b6e565fbde01f6299e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:BXRGWKNJHTMDXHPK5J3Y56TJMG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning from Video and Text via Large-Scale Discriminative Clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Antoine Miech, Ivan Laptev, Jean-Baptiste Alayrac, Josef Sivic, Piotr Bojanowski","submitted_at":"2017-07-27T23:30:53Z","abstract_excerpt":"Discriminative clustering has been successfully applied to a number of weakly-supervised learning tasks. Such applications include person and action recognition, text-to-video alignment, object co-segmentation and colocalization in videos and images. One drawback of discriminative clustering, however, is its limited scalability. We address this issue and propose an online optimization algorithm based on the Block-Coordinate Frank-Wolfe algorithm. We apply the proposed method to the problem of weakly supervised learning of actions and actors from movies together with corresponding movie scripts"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.09074","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":""},"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":"2026-05-18T00:39:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4ihHly3JgJTwQE3uwwh+dGKlF9MSZDIyWXY9PLIOfpUzBT4vwdjuaXamA9LgyUlQ8lVl/CtXUUkg1ftgQnO6DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T04:03:58.333351Z"},"content_sha256":"925062b90e063f60cfe2b1f78bdbef119916411d8e3f2f593c40ea94afabc436","schema_version":"1.0","event_id":"sha256:925062b90e063f60cfe2b1f78bdbef119916411d8e3f2f593c40ea94afabc436"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/bundle.json","state_url":"https://pith.science/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/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":"2026-06-08T04:03:58Z","links":{"resolver":"https://pith.science/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG","bundle":"https://pith.science/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/bundle.json","state":"https://pith.science/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BXRGWKNJHTMDXHPK5J3Y56TJMG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:BXRGWKNJHTMDXHPK5J3Y56TJMG","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":"ee7c046d1dca564358cca6fc5a9ca961b0498bcf0a2d99d75e0436e260a0ed29","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-27T23:30:53Z","title_canon_sha256":"b94f2cd5165c8bef76acaa4732bd61c2ecaec17c2290e0ba5391957907d5a296"},"schema_version":"1.0","source":{"id":"1707.09074","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.09074","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"arxiv_version","alias_value":"1707.09074v1","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.09074","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"pith_short_12","alias_value":"BXRGWKNJHTMD","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BXRGWKNJHTMDXHPK","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BXRGWKNJ","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:925062b90e063f60cfe2b1f78bdbef119916411d8e3f2f593c40ea94afabc436","target":"graph","created_at":"2026-05-18T00:39:17Z","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":"Discriminative clustering has been successfully applied to a number of weakly-supervised learning tasks. Such applications include person and action recognition, text-to-video alignment, object co-segmentation and colocalization in videos and images. One drawback of discriminative clustering, however, is its limited scalability. We address this issue and propose an online optimization algorithm based on the Block-Coordinate Frank-Wolfe algorithm. We apply the proposed method to the problem of weakly supervised learning of actions and actors from movies together with corresponding movie scripts","authors_text":"Antoine Miech, Ivan Laptev, Jean-Baptiste Alayrac, Josef Sivic, Piotr Bojanowski","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-27T23:30:53Z","title":"Learning from Video and Text via Large-Scale Discriminative Clustering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.09074","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":"sha256:54888a82ab90c574d7aa7a433deea26c026ddd8638d54b6e565fbde01f6299e9","target":"record","created_at":"2026-05-18T00:39:17Z","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":"ee7c046d1dca564358cca6fc5a9ca961b0498bcf0a2d99d75e0436e260a0ed29","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-27T23:30:53Z","title_canon_sha256":"b94f2cd5165c8bef76acaa4732bd61c2ecaec17c2290e0ba5391957907d5a296"},"schema_version":"1.0","source":{"id":"1707.09074","kind":"arxiv","version":1}},"canonical_sha256":"0de26b29a93cd83b9deaea778efa69618927fca0be323358c1f4088457558088","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0de26b29a93cd83b9deaea778efa69618927fca0be323358c1f4088457558088","first_computed_at":"2026-05-18T00:39:17.183987Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:17.183987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WuZCE5jzAXuWfuQR5cEhlfqssm1OAXove+G9zvQrPZifhbxsrUHTPaDNWJ2vvYnR0acGx5lfCBOMPw6wSov2Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:17.184707Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.09074","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54888a82ab90c574d7aa7a433deea26c026ddd8638d54b6e565fbde01f6299e9","sha256:925062b90e063f60cfe2b1f78bdbef119916411d8e3f2f593c40ea94afabc436"],"state_sha256":"0c9e2f217d848e04ac434db2cce538046b6a50102382c8be6484c2d3f607eecb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bmrrKWu7t3SBzM7qq1hQ0t79x7eHa0ptXtcREgVZFXMc71BfMtoXhk31nymWMQwR6nDMKD+6QO8I8pZRNpDVAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T04:03:58.337795Z","bundle_sha256":"574c3d5a38417b22ac7f31efbbfd74bc1c91fb8bc7f5a72b4b9430640a462048"}}