{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:2K4UEHXA4KZ34L55CS2J72N22M","short_pith_number":"pith:2K4UEHXA","canonical_record":{"source":{"id":"2004.00163","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-31T23:36:04Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"6d7884cd7bc755226e27efaec23167142816e7d1d48a1ed6e84951d4ec8e6988","abstract_canon_sha256":"34f68561713b1272796c4cf231453aa8700c5a749b9ef035cf5e7472d1b0ff02"},"schema_version":"1.0"},"canonical_sha256":"d2b9421ee0e2b3be2fbd14b49fe9bad337a05893c3f91719f8b7a8fc994d5cb2","source":{"kind":"arxiv","id":"2004.00163","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00163","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00163v2","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00163","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"2K4UEHXA4KZ3","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"2K4UEHXA4KZ34L55","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"2K4UEHXA","created_at":"2026-07-05T02:01:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:2K4UEHXA4KZ34L55CS2J72N22M","target":"record","payload":{"canonical_record":{"source":{"id":"2004.00163","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-31T23:36:04Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"6d7884cd7bc755226e27efaec23167142816e7d1d48a1ed6e84951d4ec8e6988","abstract_canon_sha256":"34f68561713b1272796c4cf231453aa8700c5a749b9ef035cf5e7472d1b0ff02"},"schema_version":"1.0"},"canonical_sha256":"d2b9421ee0e2b3be2fbd14b49fe9bad337a05893c3f91719f8b7a8fc994d5cb2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:01:11.241953Z","signature_b64":"sAJLopx1GR/6rBGz74Jrbr+gXfomxqoAGWDAY0oKq/or7fWk3oOs+YAKmQkf9JIozYiYLOkhbYUJ5D8GDy9RBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d2b9421ee0e2b3be2fbd14b49fe9bad337a05893c3f91719f8b7a8fc994d5cb2","last_reissued_at":"2026-07-05T02:01:11.241469Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:01:11.241469Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.00163","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":"2026-07-05T02:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6ndmRM/dg/aQuuO5rl2RH5pF/XWteCGnxoNVBI7XrV0pWa34t7RXWyOEZKEkANbdQherh94fohGQfi74MBtACA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:29:41.802711Z"},"content_sha256":"9104aaa3c10b0ade76f258d561fa554db9d3e9a13016d644ad02021bc032fad0","schema_version":"1.0","event_id":"sha256:9104aaa3c10b0ade76f258d561fa554db9d3e9a13016d644ad02021bc032fad0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:2K4UEHXA4KZ34L55CS2J72N22M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Baifeng Shi, Devin Guillory, Fang Wan, Huijuan Xu, Trevor Darrell, Wei Ke, Zhekun Luo","submitted_at":"2020-03-31T23:36:04Z","abstract_excerpt":"Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multiple Instance Learning (MIL) framework, where a bag (video) contains multiple instances (action segments). Since only the bag's label is known, the main challenge is assigning which key instances within the bag to trigger the bag's label. Most previous models use attention-based approaches applying attentions to generate the bag's representation from instances, and then train it via the bag's classification. These model"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00163","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2004.00163/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":"2026-07-05T02:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TcagX4/iF/43XaS5QFD3sSX2RUXObmB/GuXwUTX53n7rEM7j9WTqVB0OYE94iTqQ7YA7zGM11ZrEcb9zQKLCAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:29:41.803711Z"},"content_sha256":"81f09cd3c2d497e28fcc5ad4f030179e282efacb0bc68a12963212f995ab5619","schema_version":"1.0","event_id":"sha256:81f09cd3c2d497e28fcc5ad4f030179e282efacb0bc68a12963212f995ab5619"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2K4UEHXA4KZ34L55CS2J72N22M/bundle.json","state_url":"https://pith.science/pith/2K4UEHXA4KZ34L55CS2J72N22M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2K4UEHXA4KZ34L55CS2J72N22M/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":"2026-08-10T18:29:41Z","links":{"resolver":"https://pith.science/pith/2K4UEHXA4KZ34L55CS2J72N22M","bundle":"https://pith.science/pith/2K4UEHXA4KZ34L55CS2J72N22M/bundle.json","state":"https://pith.science/pith/2K4UEHXA4KZ34L55CS2J72N22M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2K4UEHXA4KZ34L55CS2J72N22M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:2K4UEHXA4KZ34L55CS2J72N22M","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":"34f68561713b1272796c4cf231453aa8700c5a749b9ef035cf5e7472d1b0ff02","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-31T23:36:04Z","title_canon_sha256":"6d7884cd7bc755226e27efaec23167142816e7d1d48a1ed6e84951d4ec8e6988"},"schema_version":"1.0","source":{"id":"2004.00163","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00163","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00163v2","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00163","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"2K4UEHXA4KZ3","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"2K4UEHXA4KZ34L55","created_at":"2026-07-05T02:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"2K4UEHXA","created_at":"2026-07-05T02:01:11Z"}],"graph_snapshots":[{"event_id":"sha256:81f09cd3c2d497e28fcc5ad4f030179e282efacb0bc68a12963212f995ab5619","target":"graph","created_at":"2026-07-05T02:01:11Z","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/2004.00163/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multiple Instance Learning (MIL) framework, where a bag (video) contains multiple instances (action segments). Since only the bag's label is known, the main challenge is assigning which key instances within the bag to trigger the bag's label. Most previous models use attention-based approaches applying attentions to generate the bag's representation from instances, and then train it via the bag's classification. These model","authors_text":"Baifeng Shi, Devin Guillory, Fang Wan, Huijuan Xu, Trevor Darrell, Wei Ke, Zhekun Luo","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-31T23:36:04Z","title":"Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00163","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":"sha256:9104aaa3c10b0ade76f258d561fa554db9d3e9a13016d644ad02021bc032fad0","target":"record","created_at":"2026-07-05T02:01:11Z","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":"34f68561713b1272796c4cf231453aa8700c5a749b9ef035cf5e7472d1b0ff02","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-31T23:36:04Z","title_canon_sha256":"6d7884cd7bc755226e27efaec23167142816e7d1d48a1ed6e84951d4ec8e6988"},"schema_version":"1.0","source":{"id":"2004.00163","kind":"arxiv","version":2}},"canonical_sha256":"d2b9421ee0e2b3be2fbd14b49fe9bad337a05893c3f91719f8b7a8fc994d5cb2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d2b9421ee0e2b3be2fbd14b49fe9bad337a05893c3f91719f8b7a8fc994d5cb2","first_computed_at":"2026-07-05T02:01:11.241469Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:01:11.241469Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sAJLopx1GR/6rBGz74Jrbr+gXfomxqoAGWDAY0oKq/or7fWk3oOs+YAKmQkf9JIozYiYLOkhbYUJ5D8GDy9RBw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:01:11.241953Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.00163","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9104aaa3c10b0ade76f258d561fa554db9d3e9a13016d644ad02021bc032fad0","sha256:81f09cd3c2d497e28fcc5ad4f030179e282efacb0bc68a12963212f995ab5619"],"state_sha256":"c9ccf389ea5d86d9532b5b297f60be0d4fdd5c896d8b9e9d91ca0fde864f0e4e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+UKXnEqrV808ArHkE2nOEnCo0KmX+ehbl+i0Ng+q1nFQCnjz/jx9ZrirXEOsaRInbLZpirqh/A/fghAFnXz2Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T18:29:41.810087Z","bundle_sha256":"b8c13e18dc5e875d8b00c347b793d7573135eacb909649f7dccf88e68dcc4bbb"}}