{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZXRKDWK56UODJGPESPMCL6SIUJ","short_pith_number":"pith:ZXRKDWK5","canonical_record":{"source":{"id":"2507.23237","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-31T04:29:49Z","cross_cats_sorted":[],"title_canon_sha256":"f46a74a528bcefcfdfe98c947444067e7c5c38d292c6c2e2a7054f13fe13d479","abstract_canon_sha256":"6b94592679eb2fc3dfe7c9b70528f1d459348e32b37e9c8bfa911bd2db683799"},"schema_version":"1.0"},"canonical_sha256":"cde2a1d95df51c3499e493d825fa48a275968e6739d87db9fbdc773f271d19a8","source":{"kind":"arxiv","id":"2507.23237","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.23237","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"arxiv_version","alias_value":"2507.23237v1","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.23237","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_12","alias_value":"ZXRKDWK56UOD","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_16","alias_value":"ZXRKDWK56UODJGPE","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_8","alias_value":"ZXRKDWK5","created_at":"2026-07-05T11:46:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZXRKDWK56UODJGPESPMCL6SIUJ","target":"record","payload":{"canonical_record":{"source":{"id":"2507.23237","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-31T04:29:49Z","cross_cats_sorted":[],"title_canon_sha256":"f46a74a528bcefcfdfe98c947444067e7c5c38d292c6c2e2a7054f13fe13d479","abstract_canon_sha256":"6b94592679eb2fc3dfe7c9b70528f1d459348e32b37e9c8bfa911bd2db683799"},"schema_version":"1.0"},"canonical_sha256":"cde2a1d95df51c3499e493d825fa48a275968e6739d87db9fbdc773f271d19a8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:46:08.085190Z","signature_b64":"Dj4eMKq/1EcIuOtEjiD0iUwobcrxDUnzlcytt0O/n08LEQuHiDt5VYIuxH6B8O2ZaxGB/7cFyrBA27KBHLT0Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cde2a1d95df51c3499e493d825fa48a275968e6739d87db9fbdc773f271d19a8","last_reissued_at":"2026-07-05T11:46:08.084694Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:46:08.084694Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.23237","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":"2026-07-05T11:46:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PtHlfhwVhM997EW29oV4Jcbz5xEt9RqT+xD1wHCayRAhSD3KYnSo1+3fzX7MLsmMkeXOIqdMxk9Lwbaxgfb/Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:28:25.082937Z"},"content_sha256":"122883b3dce56ad0a5563fbe8fcee9064b537fbef380b63956055a85138e9179","schema_version":"1.0","event_id":"sha256:122883b3dce56ad0a5563fbe8fcee9064b537fbef380b63956055a85138e9179"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZXRKDWK56UODJGPESPMCL6SIUJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Ambiguity-Guided Learnable Distribution Calibration for Semi-Supervised Few-Shot Class-Incremental Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chengyan Liu, Fan Lyu, Fuyuan Hu, Jian Zhang, Liang Wang, Linglan Zhao, Yinying Mei, Zhang Zhang","submitted_at":"2025-07-31T04:29:49Z","abstract_excerpt":"Few-Shot Class-Incremental Learning (FSCIL) focuses on models learning new concepts from limited data while retaining knowledge of previous classes. Recently, many studies have started to leverage unlabeled samples to assist models in learning from few-shot samples, giving rise to the field of Semi-supervised Few-shot Class-Incremental Learning (Semi-FSCIL). However, these studies often assume that the source of unlabeled data is only confined to novel classes of the current session, which presents a narrow perspective and cannot align well with practical scenarios. To better reflect real-worl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.23237","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/2507.23237/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":"2026-07-05T11:46:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ubMrTVksIBAAn8RZPiICT25+xlv2tMm69877PKZ/lZYLJEohNJDQ3gCydaBYAVKzZPfYi99oVXgDSon7FX8hCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:28:25.083512Z"},"content_sha256":"22e2fdd0a35e6ff597e8d97c888ec53468d8235989a0094721d6de08b70973a7","schema_version":"1.0","event_id":"sha256:22e2fdd0a35e6ff597e8d97c888ec53468d8235989a0094721d6de08b70973a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/bundle.json","state_url":"https://pith.science/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/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":"2026-08-16T11:28:25Z","links":{"resolver":"https://pith.science/pith/ZXRKDWK56UODJGPESPMCL6SIUJ","bundle":"https://pith.science/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/bundle.json","state":"https://pith.science/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZXRKDWK56UODJGPESPMCL6SIUJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZXRKDWK56UODJGPESPMCL6SIUJ","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":"6b94592679eb2fc3dfe7c9b70528f1d459348e32b37e9c8bfa911bd2db683799","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-31T04:29:49Z","title_canon_sha256":"f46a74a528bcefcfdfe98c947444067e7c5c38d292c6c2e2a7054f13fe13d479"},"schema_version":"1.0","source":{"id":"2507.23237","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.23237","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"arxiv_version","alias_value":"2507.23237v1","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.23237","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_12","alias_value":"ZXRKDWK56UOD","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_16","alias_value":"ZXRKDWK56UODJGPE","created_at":"2026-07-05T11:46:08Z"},{"alias_kind":"pith_short_8","alias_value":"ZXRKDWK5","created_at":"2026-07-05T11:46:08Z"}],"graph_snapshots":[{"event_id":"sha256:22e2fdd0a35e6ff597e8d97c888ec53468d8235989a0094721d6de08b70973a7","target":"graph","created_at":"2026-07-05T11:46:08Z","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/2507.23237/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-Shot Class-Incremental Learning (FSCIL) focuses on models learning new concepts from limited data while retaining knowledge of previous classes. Recently, many studies have started to leverage unlabeled samples to assist models in learning from few-shot samples, giving rise to the field of Semi-supervised Few-shot Class-Incremental Learning (Semi-FSCIL). However, these studies often assume that the source of unlabeled data is only confined to novel classes of the current session, which presents a narrow perspective and cannot align well with practical scenarios. To better reflect real-worl","authors_text":"Chengyan Liu, Fan Lyu, Fuyuan Hu, Jian Zhang, Liang Wang, Linglan Zhao, Yinying Mei, Zhang Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-31T04:29:49Z","title":"Ambiguity-Guided Learnable Distribution Calibration for Semi-Supervised Few-Shot Class-Incremental Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.23237","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":"sha256:122883b3dce56ad0a5563fbe8fcee9064b537fbef380b63956055a85138e9179","target":"record","created_at":"2026-07-05T11:46:08Z","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":"6b94592679eb2fc3dfe7c9b70528f1d459348e32b37e9c8bfa911bd2db683799","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-31T04:29:49Z","title_canon_sha256":"f46a74a528bcefcfdfe98c947444067e7c5c38d292c6c2e2a7054f13fe13d479"},"schema_version":"1.0","source":{"id":"2507.23237","kind":"arxiv","version":1}},"canonical_sha256":"cde2a1d95df51c3499e493d825fa48a275968e6739d87db9fbdc773f271d19a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cde2a1d95df51c3499e493d825fa48a275968e6739d87db9fbdc773f271d19a8","first_computed_at":"2026-07-05T11:46:08.084694Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:08.084694Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Dj4eMKq/1EcIuOtEjiD0iUwobcrxDUnzlcytt0O/n08LEQuHiDt5VYIuxH6B8O2ZaxGB/7cFyrBA27KBHLT0Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:08.085190Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.23237","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:122883b3dce56ad0a5563fbe8fcee9064b537fbef380b63956055a85138e9179","sha256:22e2fdd0a35e6ff597e8d97c888ec53468d8235989a0094721d6de08b70973a7"],"state_sha256":"fe3ce1dcee7dc7f4a051bcd4cdd2cf58e235c1e155a011d46ad69633664ac2cd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WZoRX6Z2Mw5podV0dmiUzylTaa1yVuRrK+hqSOZwHWQ3HwYRjSS6UhMOEJ0ydMGT+HWzj5+yx0rBLiqvoRYJCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T11:28:25.086970Z","bundle_sha256":"0214ac123bc54b04ba2841c582fd625245ccb621c721ca3723e37f921e66ae51"}}