{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:AQ65BYS4VJYXFBKJ7N2UNWFEBA","short_pith_number":"pith:AQ65BYS4","canonical_record":{"source":{"id":"1611.04871","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-12T07:39:50Z","cross_cats_sorted":["cs.CV","cs.SD"],"title_canon_sha256":"d88719cbdaa0808c684729769f4633678e75171ae8da2c15a11bda448bc382ec","abstract_canon_sha256":"7ddb0b0a07fd063a782347fd2ad3224c040ab81cb89c6fe925789fc134adbdca"},"schema_version":"1.0"},"canonical_sha256":"043dd0e25caa71728549fb7546d8a4081499e7b7536dfd9213121585359eebe9","source":{"kind":"arxiv","id":"1611.04871","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.04871","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"arxiv_version","alias_value":"1611.04871v3","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.04871","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"pith_short_12","alias_value":"AQ65BYS4VJYX","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AQ65BYS4VJYXFBKJ","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AQ65BYS4","created_at":"2026-05-18T12:30:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:AQ65BYS4VJYXFBKJ7N2UNWFEBA","target":"record","payload":{"canonical_record":{"source":{"id":"1611.04871","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-12T07:39:50Z","cross_cats_sorted":["cs.CV","cs.SD"],"title_canon_sha256":"d88719cbdaa0808c684729769f4633678e75171ae8da2c15a11bda448bc382ec","abstract_canon_sha256":"7ddb0b0a07fd063a782347fd2ad3224c040ab81cb89c6fe925789fc134adbdca"},"schema_version":"1.0"},"canonical_sha256":"043dd0e25caa71728549fb7546d8a4081499e7b7536dfd9213121585359eebe9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:30.798796Z","signature_b64":"U3OOTjzrJlgr0hTVS70UptIGrYB1aH/gjUHS4kOT0P8fT8nTRs9cNpGADJrt67gUlx160u+6A8kNhqUWD9VNCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"043dd0e25caa71728549fb7546d8a4081499e7b7536dfd9213121585359eebe9","last_reissued_at":"2026-05-18T00:50:30.798038Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:30.798038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.04871","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:50:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WLmNfNPNnOGYDaY+bjyf1SHQ5bBq3qBEl8mSTzlTHGBnwoeMuDy19olZPhJ2Wm/gJi256g410aJkT0xW5aVBDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:32:41.290585Z"},"content_sha256":"46c06075d83433ab91e076a539e9f1845364ea06a2f2f24f87b9366a684c44bb","schema_version":"1.0","event_id":"sha256:46c06075d83433ab91e076a539e9f1845364ea06a2f2f24f87b9366a684c44bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:AQ65BYS4VJYXFBKJ7N2UNWFEBA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Audio Event and Scene Recognition: A Unified Approach using Strongly and Weakly Labeled Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.SD"],"primary_cat":"cs.LG","authors_text":"Anurag Kumar, Bhiksha Raj","submitted_at":"2016-11-12T07:39:50Z","abstract_excerpt":"In this paper we propose a novel learning framework called Supervised and Weakly Supervised Learning where the goal is to learn simultaneously from weakly and strongly labeled data. Strongly labeled data can be simply understood as fully supervised data where all labeled instances are available. In weakly supervised learning only data is weakly labeled which prevents one from directly applying supervised learning methods. Our proposed framework is motivated by the fact that a small amount of strongly labeled data can give considerable improvement over only weakly supervised learning. The prima"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.04871","kind":"arxiv","version":3},"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":"2026-05-18T00:50:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yy5UIJcQNsJNAjM+XztsNtOi+YDQqokCVaBGa8yGr7KAL+DWfYwFEWy9tsNYaEm8Eyo7OCDYhkoYbJYGaSwgAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:32:41.291402Z"},"content_sha256":"bb2cb33298063b15617b9e2cd8a8bb5298a1311fdb84ad0295cf21b3d4c1781d","schema_version":"1.0","event_id":"sha256:bb2cb33298063b15617b9e2cd8a8bb5298a1311fdb84ad0295cf21b3d4c1781d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/bundle.json","state_url":"https://pith.science/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/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":"2026-05-31T13:32:41Z","links":{"resolver":"https://pith.science/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA","bundle":"https://pith.science/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/bundle.json","state":"https://pith.science/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AQ65BYS4VJYXFBKJ7N2UNWFEBA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:AQ65BYS4VJYXFBKJ7N2UNWFEBA","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":"7ddb0b0a07fd063a782347fd2ad3224c040ab81cb89c6fe925789fc134adbdca","cross_cats_sorted":["cs.CV","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-12T07:39:50Z","title_canon_sha256":"d88719cbdaa0808c684729769f4633678e75171ae8da2c15a11bda448bc382ec"},"schema_version":"1.0","source":{"id":"1611.04871","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.04871","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"arxiv_version","alias_value":"1611.04871v3","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.04871","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"pith_short_12","alias_value":"AQ65BYS4VJYX","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AQ65BYS4VJYXFBKJ","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AQ65BYS4","created_at":"2026-05-18T12:30:07Z"}],"graph_snapshots":[{"event_id":"sha256:bb2cb33298063b15617b9e2cd8a8bb5298a1311fdb84ad0295cf21b3d4c1781d","target":"graph","created_at":"2026-05-18T00:50:30Z","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":"In this paper we propose a novel learning framework called Supervised and Weakly Supervised Learning where the goal is to learn simultaneously from weakly and strongly labeled data. Strongly labeled data can be simply understood as fully supervised data where all labeled instances are available. In weakly supervised learning only data is weakly labeled which prevents one from directly applying supervised learning methods. Our proposed framework is motivated by the fact that a small amount of strongly labeled data can give considerable improvement over only weakly supervised learning. The prima","authors_text":"Anurag Kumar, Bhiksha Raj","cross_cats":["cs.CV","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-12T07:39:50Z","title":"Audio Event and Scene Recognition: A Unified Approach using Strongly and Weakly Labeled Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.04871","kind":"arxiv","version":3},"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":"sha256:46c06075d83433ab91e076a539e9f1845364ea06a2f2f24f87b9366a684c44bb","target":"record","created_at":"2026-05-18T00:50:30Z","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":"7ddb0b0a07fd063a782347fd2ad3224c040ab81cb89c6fe925789fc134adbdca","cross_cats_sorted":["cs.CV","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-12T07:39:50Z","title_canon_sha256":"d88719cbdaa0808c684729769f4633678e75171ae8da2c15a11bda448bc382ec"},"schema_version":"1.0","source":{"id":"1611.04871","kind":"arxiv","version":3}},"canonical_sha256":"043dd0e25caa71728549fb7546d8a4081499e7b7536dfd9213121585359eebe9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"043dd0e25caa71728549fb7546d8a4081499e7b7536dfd9213121585359eebe9","first_computed_at":"2026-05-18T00:50:30.798038Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:50:30.798038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U3OOTjzrJlgr0hTVS70UptIGrYB1aH/gjUHS4kOT0P8fT8nTRs9cNpGADJrt67gUlx160u+6A8kNhqUWD9VNCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:50:30.798796Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.04871","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46c06075d83433ab91e076a539e9f1845364ea06a2f2f24f87b9366a684c44bb","sha256:bb2cb33298063b15617b9e2cd8a8bb5298a1311fdb84ad0295cf21b3d4c1781d"],"state_sha256":"4838d4e39185fea51d406761dd8ca5ebc13f9d860accdd463fa366bf5d47f707"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zrE0GZGksXZEX/inmxuy9yfwzOnSQf1TsSumef+ywAzPuxgOxI5LzMJBaseUQamBFFe+Yvw/3NaQWXVevXirDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T13:32:41.295909Z","bundle_sha256":"b29b495fe60aa75b976971488f37956a52e4a59e2722fb702fd9de150c138e0e"}}