{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:PDCNO46C2U45IGCZCS2OWXCLGX","short_pith_number":"pith:PDCNO46C","canonical_record":{"source":{"id":"2106.00609","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-01T16:22:01Z","cross_cats_sorted":[],"title_canon_sha256":"2bf8bf2fbda6830240c1f833d308e28f7902edb3af4e3b3fca07d28bb2eb7a8c","abstract_canon_sha256":"d3466e2d6f99b2f31840b23dddf041ac3052c7933dadec0d5b6b1cd2809f98e7"},"schema_version":"1.0"},"canonical_sha256":"78c4d773c2d539d4185914b4eb5c4b35c0bade361f0d1e45f07a4d4fd75cdefe","source":{"kind":"arxiv","id":"2106.00609","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00609","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00609v2","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00609","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_12","alias_value":"PDCNO46C2U45","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_16","alias_value":"PDCNO46C2U45IGCZ","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_8","alias_value":"PDCNO46C","created_at":"2026-07-05T03:43:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:PDCNO46C2U45IGCZCS2OWXCLGX","target":"record","payload":{"canonical_record":{"source":{"id":"2106.00609","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-01T16:22:01Z","cross_cats_sorted":[],"title_canon_sha256":"2bf8bf2fbda6830240c1f833d308e28f7902edb3af4e3b3fca07d28bb2eb7a8c","abstract_canon_sha256":"d3466e2d6f99b2f31840b23dddf041ac3052c7933dadec0d5b6b1cd2809f98e7"},"schema_version":"1.0"},"canonical_sha256":"78c4d773c2d539d4185914b4eb5c4b35c0bade361f0d1e45f07a4d4fd75cdefe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:43:41.401775Z","signature_b64":"aO/rlKn/3yKJRGLL4Xdc9PGyww4zinM6ORLmBAVWG86ovMQpu07MZm1HPTdR/W4nOSZLpOu8gHZvLtV7A8FhDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"78c4d773c2d539d4185914b4eb5c4b35c0bade361f0d1e45f07a4d4fd75cdefe","last_reissued_at":"2026-07-05T03:43:41.401340Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:43:41.401340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.00609","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":"2026-07-05T03:43:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yJ2gQvOYiGVJP9jNptdxGqUDs3tpB8a9H8B/UdRdTC5jM+9I3VKFPKZzmnwCi0Rk4UPCJrMn+CTdw5a0QsPaDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:22:01.775977Z"},"content_sha256":"3f46b467c05107e58a9c265ca001b75563459c53928d37ee018ba4c17062f20f","schema_version":"1.0","event_id":"sha256:3f46b467c05107e58a9c265ca001b75563459c53928d37ee018ba4c17062f20f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:PDCNO46C2U45IGCZCS2OWXCLGX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Mutual Learning for Semi-supervised Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Zhang, Dong Chen, Fang Wen, Pan Zhang, Ting Zhang","submitted_at":"2021-06-01T16:22:01Z","abstract_excerpt":"Recent semi-supervised learning (SSL) methods are commonly based on pseudo labeling. Since the SSL performance is greatly influenced by the quality of pseudo labels, mutual learning has been proposed to effectively suppress the noises in the pseudo supervision. In this work, we propose robust mutual learning that improves the prior approach in two aspects. First, the vanilla mutual learners suffer from the coupling issue that models may converge to learn homogeneous knowledge. We resolve this issue by introducing mean teachers to generate mutual supervisions so that there is no direct interact"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00609","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/2106.00609/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":"2026-07-05T03:43:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uQB2kT2wq4BDjp0FLlfTJVqBGrJW77qanTiCif8ZPai/rLnhh/T5TkhuN4ySIZQnraVeyCKvzrZ3ZSpvzhDXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:22:01.776524Z"},"content_sha256":"94bec66c507f9121c36270eaf684e4d8ad2f014ce34f9d506dd126e8c0565910","schema_version":"1.0","event_id":"sha256:94bec66c507f9121c36270eaf684e4d8ad2f014ce34f9d506dd126e8c0565910"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PDCNO46C2U45IGCZCS2OWXCLGX/bundle.json","state_url":"https://pith.science/pith/PDCNO46C2U45IGCZCS2OWXCLGX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PDCNO46C2U45IGCZCS2OWXCLGX/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":"2026-08-04T06:22:01Z","links":{"resolver":"https://pith.science/pith/PDCNO46C2U45IGCZCS2OWXCLGX","bundle":"https://pith.science/pith/PDCNO46C2U45IGCZCS2OWXCLGX/bundle.json","state":"https://pith.science/pith/PDCNO46C2U45IGCZCS2OWXCLGX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PDCNO46C2U45IGCZCS2OWXCLGX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:PDCNO46C2U45IGCZCS2OWXCLGX","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":"d3466e2d6f99b2f31840b23dddf041ac3052c7933dadec0d5b6b1cd2809f98e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-01T16:22:01Z","title_canon_sha256":"2bf8bf2fbda6830240c1f833d308e28f7902edb3af4e3b3fca07d28bb2eb7a8c"},"schema_version":"1.0","source":{"id":"2106.00609","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00609","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00609v2","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00609","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_12","alias_value":"PDCNO46C2U45","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_16","alias_value":"PDCNO46C2U45IGCZ","created_at":"2026-07-05T03:43:41Z"},{"alias_kind":"pith_short_8","alias_value":"PDCNO46C","created_at":"2026-07-05T03:43:41Z"}],"graph_snapshots":[{"event_id":"sha256:94bec66c507f9121c36270eaf684e4d8ad2f014ce34f9d506dd126e8c0565910","target":"graph","created_at":"2026-07-05T03:43:41Z","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/2106.00609/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent semi-supervised learning (SSL) methods are commonly based on pseudo labeling. Since the SSL performance is greatly influenced by the quality of pseudo labels, mutual learning has been proposed to effectively suppress the noises in the pseudo supervision. In this work, we propose robust mutual learning that improves the prior approach in two aspects. First, the vanilla mutual learners suffer from the coupling issue that models may converge to learn homogeneous knowledge. We resolve this issue by introducing mean teachers to generate mutual supervisions so that there is no direct interact","authors_text":"Bo Zhang, Dong Chen, Fang Wen, Pan Zhang, Ting Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-01T16:22:01Z","title":"Robust Mutual Learning for Semi-supervised Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00609","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":"sha256:3f46b467c05107e58a9c265ca001b75563459c53928d37ee018ba4c17062f20f","target":"record","created_at":"2026-07-05T03:43:41Z","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":"d3466e2d6f99b2f31840b23dddf041ac3052c7933dadec0d5b6b1cd2809f98e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-01T16:22:01Z","title_canon_sha256":"2bf8bf2fbda6830240c1f833d308e28f7902edb3af4e3b3fca07d28bb2eb7a8c"},"schema_version":"1.0","source":{"id":"2106.00609","kind":"arxiv","version":2}},"canonical_sha256":"78c4d773c2d539d4185914b4eb5c4b35c0bade361f0d1e45f07a4d4fd75cdefe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"78c4d773c2d539d4185914b4eb5c4b35c0bade361f0d1e45f07a4d4fd75cdefe","first_computed_at":"2026-07-05T03:43:41.401340Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:43:41.401340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aO/rlKn/3yKJRGLL4Xdc9PGyww4zinM6ORLmBAVWG86ovMQpu07MZm1HPTdR/W4nOSZLpOu8gHZvLtV7A8FhDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:43:41.401775Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.00609","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3f46b467c05107e58a9c265ca001b75563459c53928d37ee018ba4c17062f20f","sha256:94bec66c507f9121c36270eaf684e4d8ad2f014ce34f9d506dd126e8c0565910"],"state_sha256":"c782dfe191ec4ce2e5acc373679cec536ce146cb0913ed46a0d36d61a637a8e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FpZI4epooMzkAkICyLJ4myY0Udc1BUgyR6kl7roBI7n0CEwauEWaJzBnQ18knYOdT4BxQGdorYv36puvkgw5Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T06:22:01.783205Z","bundle_sha256":"138dfca24662fa7816019da5d37301fdd0302061dd3576da00bb18fe953674c5"}}