{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:5CT35DFY6L3X6ESY2GK35SBKFN","short_pith_number":"pith:5CT35DFY","canonical_record":{"source":{"id":"2205.13750","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-27T03:29:17Z","cross_cats_sorted":[],"title_canon_sha256":"6e7629d16b8a889da652a246effa74aa472f84b815ba794b023a75f0317f3141","abstract_canon_sha256":"98586f9b762c644f0245b9c7353eb249958ae90b7a1c5bc42d39aea486a7d796"},"schema_version":"1.0"},"canonical_sha256":"e8a7be8cb8f2f77f1258d195bec82a2b611981d09f36d7e0e63e08a18a1319a1","source":{"kind":"arxiv","id":"2205.13750","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.13750","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2205.13750v1","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.13750","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"5CT35DFY6L3X","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"5CT35DFY6L3X6ESY","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"5CT35DFY","created_at":"2026-07-05T04:26:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:5CT35DFY6L3X6ESY2GK35SBKFN","target":"record","payload":{"canonical_record":{"source":{"id":"2205.13750","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-27T03:29:17Z","cross_cats_sorted":[],"title_canon_sha256":"6e7629d16b8a889da652a246effa74aa472f84b815ba794b023a75f0317f3141","abstract_canon_sha256":"98586f9b762c644f0245b9c7353eb249958ae90b7a1c5bc42d39aea486a7d796"},"schema_version":"1.0"},"canonical_sha256":"e8a7be8cb8f2f77f1258d195bec82a2b611981d09f36d7e0e63e08a18a1319a1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:51.609287Z","signature_b64":"USI60izPTELdw8Lp4Slgxwz4j0kpXiKdjVwlSDBvm6ZvnUq73+EFFz6cUuUsrbH2XkwuCdG7s/LZoxewSHJVDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8a7be8cb8f2f77f1258d195bec82a2b611981d09f36d7e0e63e08a18a1319a1","last_reissued_at":"2026-07-05T04:26:51.608817Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:51.608817Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.13750","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":"2026-07-05T04:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vlIjSP4Qe8kKc5xCgEON35RYVzE5GLbRPw/PrZlW9PrP9XF4+MQU2JBUxgb0BHjXTxj+OrH8iaEsBo/dhdGpAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T06:48:48.822950Z"},"content_sha256":"3351eb49c0bebc75731f3511baa033b6b08998302db00d6eb40f561eda508d5b","schema_version":"1.0","event_id":"sha256:3351eb49c0bebc75731f3511baa033b6b08998302db00d6eb40f561eda508d5b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:5CT35DFY6L3X6ESY2GK35SBKFN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attention Awareness Multiple Instance Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Beichen Zhou, Jingjun Yi","submitted_at":"2022-05-27T03:29:17Z","abstract_excerpt":"Multiple instance learning is qualified for many pattern recognition tasks with weakly annotated data. The combination of artificial neural network and multiple instance learning offers an end-to-end solution and has been widely utilized. However, challenges remain in two-folds. Firstly, current MIL pooling operators are usually pre-defined and lack flexibility to mine key instances. Secondly, in current solutions, the bag-level representation can be inaccurate or inaccessible. To this end, we propose an attention awareness multiple instance neural network framework in this paper. It consists "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.13750","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/2205.13750/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":"2026-07-05T04:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iWm3wQohqHU/35IvoVwqdPMkvasW21q3o20jGYznmU8LnoXj3KjFO8NReYnJi3SaO+b41z+Ef/sliO+jksflAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T06:48:48.823331Z"},"content_sha256":"8d96dfa034ea76889b94547bbd5d1099100276d39a13b1025495536554ad8cee","schema_version":"1.0","event_id":"sha256:8d96dfa034ea76889b94547bbd5d1099100276d39a13b1025495536554ad8cee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5CT35DFY6L3X6ESY2GK35SBKFN/bundle.json","state_url":"https://pith.science/pith/5CT35DFY6L3X6ESY2GK35SBKFN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5CT35DFY6L3X6ESY2GK35SBKFN/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":"2026-07-12T06:48:48Z","links":{"resolver":"https://pith.science/pith/5CT35DFY6L3X6ESY2GK35SBKFN","bundle":"https://pith.science/pith/5CT35DFY6L3X6ESY2GK35SBKFN/bundle.json","state":"https://pith.science/pith/5CT35DFY6L3X6ESY2GK35SBKFN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5CT35DFY6L3X6ESY2GK35SBKFN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5CT35DFY6L3X6ESY2GK35SBKFN","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":"98586f9b762c644f0245b9c7353eb249958ae90b7a1c5bc42d39aea486a7d796","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-27T03:29:17Z","title_canon_sha256":"6e7629d16b8a889da652a246effa74aa472f84b815ba794b023a75f0317f3141"},"schema_version":"1.0","source":{"id":"2205.13750","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.13750","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2205.13750v1","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.13750","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"5CT35DFY6L3X","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"5CT35DFY6L3X6ESY","created_at":"2026-07-05T04:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"5CT35DFY","created_at":"2026-07-05T04:26:51Z"}],"graph_snapshots":[{"event_id":"sha256:8d96dfa034ea76889b94547bbd5d1099100276d39a13b1025495536554ad8cee","target":"graph","created_at":"2026-07-05T04:26:51Z","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/2205.13750/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multiple instance learning is qualified for many pattern recognition tasks with weakly annotated data. The combination of artificial neural network and multiple instance learning offers an end-to-end solution and has been widely utilized. However, challenges remain in two-folds. Firstly, current MIL pooling operators are usually pre-defined and lack flexibility to mine key instances. Secondly, in current solutions, the bag-level representation can be inaccurate or inaccessible. To this end, we propose an attention awareness multiple instance neural network framework in this paper. It consists ","authors_text":"Beichen Zhou, Jingjun Yi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-27T03:29:17Z","title":"Attention Awareness Multiple Instance Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.13750","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":"sha256:3351eb49c0bebc75731f3511baa033b6b08998302db00d6eb40f561eda508d5b","target":"record","created_at":"2026-07-05T04:26:51Z","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":"98586f9b762c644f0245b9c7353eb249958ae90b7a1c5bc42d39aea486a7d796","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-27T03:29:17Z","title_canon_sha256":"6e7629d16b8a889da652a246effa74aa472f84b815ba794b023a75f0317f3141"},"schema_version":"1.0","source":{"id":"2205.13750","kind":"arxiv","version":1}},"canonical_sha256":"e8a7be8cb8f2f77f1258d195bec82a2b611981d09f36d7e0e63e08a18a1319a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e8a7be8cb8f2f77f1258d195bec82a2b611981d09f36d7e0e63e08a18a1319a1","first_computed_at":"2026-07-05T04:26:51.608817Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:51.608817Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"USI60izPTELdw8Lp4Slgxwz4j0kpXiKdjVwlSDBvm6ZvnUq73+EFFz6cUuUsrbH2XkwuCdG7s/LZoxewSHJVDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:51.609287Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.13750","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3351eb49c0bebc75731f3511baa033b6b08998302db00d6eb40f561eda508d5b","sha256:8d96dfa034ea76889b94547bbd5d1099100276d39a13b1025495536554ad8cee"],"state_sha256":"5ddabd1556ef4445fa808c0f08efeb3b1b440b3744742410cb72fb1d51a534b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1ks9WjbdawAPeuZ5XxD2RdjTZvHJeM6h1xM/MNpqcqoCKDeMjqSxeZPcNMIjD+WDdjFmuc4nfzpjiCWldUIgAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T06:48:48.825307Z","bundle_sha256":"f51970ef5e297cef53b8c9122f9c80cec41e891a749fe8dd1b7a7ebf81fad7c9"}}