{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:E4TWLWTAABBSLRZVKD7M6TC5YY","short_pith_number":"pith:E4TWLWTA","canonical_record":{"source":{"id":"2404.17173","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-26T06:00:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"db296e173226f8fad0d71aef10fc47a9c7e5dc584b09277065363ac30d6ed3df","abstract_canon_sha256":"5017db7f78a2b6e33a556794cf669586f5718adda7861913cb5581c83494fc22"},"schema_version":"1.0"},"canonical_sha256":"272765da60004325c73550fecf4c5dc612300a0bde058c4a34e41a76e094cdc8","source":{"kind":"arxiv","id":"2404.17173","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.17173","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"arxiv_version","alias_value":"2404.17173v1","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.17173","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_12","alias_value":"E4TWLWTAABBS","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_16","alias_value":"E4TWLWTAABBSLRZV","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_8","alias_value":"E4TWLWTA","created_at":"2026-07-05T08:12:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:E4TWLWTAABBSLRZVKD7M6TC5YY","target":"record","payload":{"canonical_record":{"source":{"id":"2404.17173","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-26T06:00:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"db296e173226f8fad0d71aef10fc47a9c7e5dc584b09277065363ac30d6ed3df","abstract_canon_sha256":"5017db7f78a2b6e33a556794cf669586f5718adda7861913cb5581c83494fc22"},"schema_version":"1.0"},"canonical_sha256":"272765da60004325c73550fecf4c5dc612300a0bde058c4a34e41a76e094cdc8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:33.942396Z","signature_b64":"DCxGZ2a8dGOFvZElUtyc1bP6QabTYALi5H2rHThySrq10RZG9DfqJhwMRsCjcyfzYoQlupK1sQ8gqoq3rbHaDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"272765da60004325c73550fecf4c5dc612300a0bde058c4a34e41a76e094cdc8","last_reissued_at":"2026-07-05T08:12:33.941967Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:33.941967Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.17173","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":"2026-07-05T08:12:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ffJg8uy8/X+8iSPgAaGqvSLeyL9GdGeoYKApT7rCdy3fAq40cFHb24rRXhEomkUSw7mt4hG4vqs250ZvoFexAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:13:13.030998Z"},"content_sha256":"e864b53cc7781281ced86b27752f18b0d22bd9dfaa636c5a467fa71e33418f57","schema_version":"1.0","event_id":"sha256:e864b53cc7781281ced86b27752f18b0d22bd9dfaa636c5a467fa71e33418f57"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:E4TWLWTAABBSLRZVKD7M6TC5YY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Fang Liu, Licheng Jiao, Lingling Li, Shuyuan Yang, Xu Liu, Yanbiao Ma","submitted_at":"2024-04-26T06:00:27Z","abstract_excerpt":"In semi-supervised learning, methods that rely on confidence learning to generate pseudo-labels have been widely proposed. However, increasing research finds that when faced with noisy and biased data, the model's representation network is more reliable than the classification network. Additionally, label generation methods based on model predictions often show poor adaptability across different datasets, necessitating customization of the classification network. Therefore, we propose a Hierarchical Dynamic Labeling (HDL) algorithm that does not depend on model predictions and utilizes image e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.17173","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/2404.17173/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":"2026-07-05T08:12:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"waL3QJV57J1OUnF/Gi+08W2OMis+3fYHm+UDBVVVfY/igp5ECWeBVzMwm7OZcZxuy4GCBEOK5rZVYLejKJtGBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:13:13.031381Z"},"content_sha256":"365fa5ee13fbba68a967858f785bc894ac20db94519492e42f276dd15bae12e3","schema_version":"1.0","event_id":"sha256:365fa5ee13fbba68a967858f785bc894ac20db94519492e42f276dd15bae12e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/bundle.json","state_url":"https://pith.science/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/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":"2026-07-07T04:13:13Z","links":{"resolver":"https://pith.science/pith/E4TWLWTAABBSLRZVKD7M6TC5YY","bundle":"https://pith.science/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/bundle.json","state":"https://pith.science/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E4TWLWTAABBSLRZVKD7M6TC5YY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:E4TWLWTAABBSLRZVKD7M6TC5YY","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":"5017db7f78a2b6e33a556794cf669586f5718adda7861913cb5581c83494fc22","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-26T06:00:27Z","title_canon_sha256":"db296e173226f8fad0d71aef10fc47a9c7e5dc584b09277065363ac30d6ed3df"},"schema_version":"1.0","source":{"id":"2404.17173","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.17173","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"arxiv_version","alias_value":"2404.17173v1","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.17173","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_12","alias_value":"E4TWLWTAABBS","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_16","alias_value":"E4TWLWTAABBSLRZV","created_at":"2026-07-05T08:12:33Z"},{"alias_kind":"pith_short_8","alias_value":"E4TWLWTA","created_at":"2026-07-05T08:12:33Z"}],"graph_snapshots":[{"event_id":"sha256:365fa5ee13fbba68a967858f785bc894ac20db94519492e42f276dd15bae12e3","target":"graph","created_at":"2026-07-05T08:12:33Z","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/2404.17173/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In semi-supervised learning, methods that rely on confidence learning to generate pseudo-labels have been widely proposed. However, increasing research finds that when faced with noisy and biased data, the model's representation network is more reliable than the classification network. Additionally, label generation methods based on model predictions often show poor adaptability across different datasets, necessitating customization of the classification network. Therefore, we propose a Hierarchical Dynamic Labeling (HDL) algorithm that does not depend on model predictions and utilizes image e","authors_text":"Fang Liu, Licheng Jiao, Lingling Li, Shuyuan Yang, Xu Liu, Yanbiao Ma","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-26T06:00:27Z","title":"Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.17173","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:e864b53cc7781281ced86b27752f18b0d22bd9dfaa636c5a467fa71e33418f57","target":"record","created_at":"2026-07-05T08:12:33Z","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":"5017db7f78a2b6e33a556794cf669586f5718adda7861913cb5581c83494fc22","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-26T06:00:27Z","title_canon_sha256":"db296e173226f8fad0d71aef10fc47a9c7e5dc584b09277065363ac30d6ed3df"},"schema_version":"1.0","source":{"id":"2404.17173","kind":"arxiv","version":1}},"canonical_sha256":"272765da60004325c73550fecf4c5dc612300a0bde058c4a34e41a76e094cdc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"272765da60004325c73550fecf4c5dc612300a0bde058c4a34e41a76e094cdc8","first_computed_at":"2026-07-05T08:12:33.941967Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:12:33.941967Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DCxGZ2a8dGOFvZElUtyc1bP6QabTYALi5H2rHThySrq10RZG9DfqJhwMRsCjcyfzYoQlupK1sQ8gqoq3rbHaDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:12:33.942396Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.17173","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e864b53cc7781281ced86b27752f18b0d22bd9dfaa636c5a467fa71e33418f57","sha256:365fa5ee13fbba68a967858f785bc894ac20db94519492e42f276dd15bae12e3"],"state_sha256":"0d5b28036fb7c97b48c556d815f85017af60b980126ec5cf4577073082c5a665"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B/PDOMIzFPpp+Zf/ufa5TXanuQN6GkI9ICJBgxYSyf1E+vtPOx5z0ihFY9/GdaR99j3dF2xCKj3wmmi1xb1VDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:13:13.033306Z","bundle_sha256":"b7ac6751978ea11c73df2ea5b71a1ede67bd4ca83a4a7539afc5d6dcf81f48c2"}}