{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DKIDNN4ILYXIH3UA6ZTEIV7FYK","short_pith_number":"pith:DKIDNN4I","canonical_record":{"source":{"id":"2410.14749","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T20:49:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2daa6e13fd8997410602b8e1f8e49d55997d6993f8b80697fe198069ffda237b","abstract_canon_sha256":"ae2b390145af66372379b56b82472394076174502150a2d6f9dff1b4d2c33e14"},"schema_version":"1.0"},"canonical_sha256":"1a9036b7885e2e83ee80f6664457e5c2912fa9d034074d9e5cf4fcdbfbb9ea60","source":{"kind":"arxiv","id":"2410.14749","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.14749","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"arxiv_version","alias_value":"2410.14749v1","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.14749","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_12","alias_value":"DKIDNN4ILYXI","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_16","alias_value":"DKIDNN4ILYXIH3UA","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_8","alias_value":"DKIDNN4I","created_at":"2026-07-05T09:23:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DKIDNN4ILYXIH3UA6ZTEIV7FYK","target":"record","payload":{"canonical_record":{"source":{"id":"2410.14749","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T20:49:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2daa6e13fd8997410602b8e1f8e49d55997d6993f8b80697fe198069ffda237b","abstract_canon_sha256":"ae2b390145af66372379b56b82472394076174502150a2d6f9dff1b4d2c33e14"},"schema_version":"1.0"},"canonical_sha256":"1a9036b7885e2e83ee80f6664457e5c2912fa9d034074d9e5cf4fcdbfbb9ea60","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:23:15.937462Z","signature_b64":"+GlJchVEP5jW0AhX9we+jIhAMJtHrNhV6HBGeRdC3JSsZID5U8kqWotpCh2JjAZniJOd0Rx8Le3e+Oc2dhlvAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a9036b7885e2e83ee80f6664457e5c2912fa9d034074d9e5cf4fcdbfbb9ea60","last_reissued_at":"2026-07-05T09:23:15.936996Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:23:15.936996Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.14749","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":"2026-07-05T09:23:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GyQICms0ZLkEcVBR+nAFnJob/ft1gvGtNz1Cqw7LNX8XKXkMb7faPUWurrKcF9mItV5mJAHOoG7K0SUKU9WPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T12:33:30.766302Z"},"content_sha256":"c66293bdeaef92a5aa0ba5fa104e82f8339e2a135dc3d80d2ab1c868bc3c3330","schema_version":"1.0","event_id":"sha256:c66293bdeaef92a5aa0ba5fa104e82f8339e2a135dc3d80d2ab1c868bc3c3330"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DKIDNN4ILYXIH3UA6ZTEIV7FYK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Leonardo Rossi, Massimo Bertozzi, Munsif Ali","submitted_at":"2024-10-17T20:49:08Z","abstract_excerpt":"Few-shot and continual learning face two well-known challenges in GANs: overfitting and catastrophic forgetting. Learning new tasks results in catastrophic forgetting in deep learning models. In the case of a few-shot setting, the model learns from a very limited number of samples (e.g. 10 samples), which can lead to overfitting and mode collapse. So, this paper proposes a Continual Few-shot Teacher-Student technique for the generative adversarial network (CFTS-GAN) that considers both challenges together. Our CFTS-GAN uses an adapter module as a student to learn a new task without affecting t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.14749","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/2410.14749/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":"2026-07-05T09:23:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7jDZJf6E3lcM7isuY2Zwr17jgOyc6pD1/qktv5AFsom3VnVaZND49AIHIutn/ys3VQpyZDqRtDodSS6Pi2LADQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T12:33:30.766674Z"},"content_sha256":"76a94ee7099f482baddaa037422364efe91dddf1ecc2c5eb829ce4bf21656a84","schema_version":"1.0","event_id":"sha256:76a94ee7099f482baddaa037422364efe91dddf1ecc2c5eb829ce4bf21656a84"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/bundle.json","state_url":"https://pith.science/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/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":"2026-08-13T12:33:30Z","links":{"resolver":"https://pith.science/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK","bundle":"https://pith.science/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/bundle.json","state":"https://pith.science/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DKIDNN4ILYXIH3UA6ZTEIV7FYK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DKIDNN4ILYXIH3UA6ZTEIV7FYK","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":"ae2b390145af66372379b56b82472394076174502150a2d6f9dff1b4d2c33e14","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T20:49:08Z","title_canon_sha256":"2daa6e13fd8997410602b8e1f8e49d55997d6993f8b80697fe198069ffda237b"},"schema_version":"1.0","source":{"id":"2410.14749","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.14749","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"arxiv_version","alias_value":"2410.14749v1","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.14749","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_12","alias_value":"DKIDNN4ILYXI","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_16","alias_value":"DKIDNN4ILYXIH3UA","created_at":"2026-07-05T09:23:15Z"},{"alias_kind":"pith_short_8","alias_value":"DKIDNN4I","created_at":"2026-07-05T09:23:15Z"}],"graph_snapshots":[{"event_id":"sha256:76a94ee7099f482baddaa037422364efe91dddf1ecc2c5eb829ce4bf21656a84","target":"graph","created_at":"2026-07-05T09:23:15Z","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/2410.14749/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-shot and continual learning face two well-known challenges in GANs: overfitting and catastrophic forgetting. Learning new tasks results in catastrophic forgetting in deep learning models. In the case of a few-shot setting, the model learns from a very limited number of samples (e.g. 10 samples), which can lead to overfitting and mode collapse. So, this paper proposes a Continual Few-shot Teacher-Student technique for the generative adversarial network (CFTS-GAN) that considers both challenges together. Our CFTS-GAN uses an adapter module as a student to learn a new task without affecting t","authors_text":"Leonardo Rossi, Massimo Bertozzi, Munsif Ali","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T20:49:08Z","title":"CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.14749","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:c66293bdeaef92a5aa0ba5fa104e82f8339e2a135dc3d80d2ab1c868bc3c3330","target":"record","created_at":"2026-07-05T09:23:15Z","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":"ae2b390145af66372379b56b82472394076174502150a2d6f9dff1b4d2c33e14","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T20:49:08Z","title_canon_sha256":"2daa6e13fd8997410602b8e1f8e49d55997d6993f8b80697fe198069ffda237b"},"schema_version":"1.0","source":{"id":"2410.14749","kind":"arxiv","version":1}},"canonical_sha256":"1a9036b7885e2e83ee80f6664457e5c2912fa9d034074d9e5cf4fcdbfbb9ea60","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a9036b7885e2e83ee80f6664457e5c2912fa9d034074d9e5cf4fcdbfbb9ea60","first_computed_at":"2026-07-05T09:23:15.936996Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:23:15.936996Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+GlJchVEP5jW0AhX9we+jIhAMJtHrNhV6HBGeRdC3JSsZID5U8kqWotpCh2JjAZniJOd0Rx8Le3e+Oc2dhlvAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:23:15.937462Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.14749","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c66293bdeaef92a5aa0ba5fa104e82f8339e2a135dc3d80d2ab1c868bc3c3330","sha256:76a94ee7099f482baddaa037422364efe91dddf1ecc2c5eb829ce4bf21656a84"],"state_sha256":"c84794ae260ffdcee51046eb8b8db4901fd198e647025f8fc5bbb456a5054c1c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rNXuIcY9qn++qPJvLGWTi+2s8L++wOO1kM4NgnCk/FMzyCjlI9a3VcKBRBsXnPI8+Psab+DRFnZ9xYmf8I/bAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T12:33:30.769830Z","bundle_sha256":"e5991aeb15c8940bcda898251be88c7766abbf8fec989a3181389cea17f592c9"}}