{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GRHFK3LN3K42MOZHFRXYX5IGL2","short_pith_number":"pith:GRHFK3LN","canonical_record":{"source":{"id":"2501.08763","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T12:33:11Z","cross_cats_sorted":[],"title_canon_sha256":"ae7e35e49a152d1c5e67b1d61cc16710fd832eba89544974d7277de7bc3fb837","abstract_canon_sha256":"72d8c15a061f8f8c137ef06e7932e91577cf9924efacb42bcab485c28567db36"},"schema_version":"1.0"},"canonical_sha256":"344e556d6ddab9a63b272c6f8bf5065e8a4707256e7d104e1ce8fd0d22fa446d","source":{"kind":"arxiv","id":"2501.08763","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.08763","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"arxiv_version","alias_value":"2501.08763v2","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.08763","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_12","alias_value":"GRHFK3LN3K42","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_16","alias_value":"GRHFK3LN3K42MOZH","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_8","alias_value":"GRHFK3LN","created_at":"2026-07-05T11:20:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GRHFK3LN3K42MOZHFRXYX5IGL2","target":"record","payload":{"canonical_record":{"source":{"id":"2501.08763","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T12:33:11Z","cross_cats_sorted":[],"title_canon_sha256":"ae7e35e49a152d1c5e67b1d61cc16710fd832eba89544974d7277de7bc3fb837","abstract_canon_sha256":"72d8c15a061f8f8c137ef06e7932e91577cf9924efacb42bcab485c28567db36"},"schema_version":"1.0"},"canonical_sha256":"344e556d6ddab9a63b272c6f8bf5065e8a4707256e7d104e1ce8fd0d22fa446d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:08.011930Z","signature_b64":"UEoeITjyDBOavdNwb5+lW9vyasXQPxIGa1agiQxx0Cf408H8LBmAsm9gfzrPE+Q+XbAvFhU9ur0SY+PoyJ1pDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"344e556d6ddab9a63b272c6f8bf5065e8a4707256e7d104e1ce8fd0d22fa446d","last_reissued_at":"2026-07-05T11:20:08.011449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:08.011449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.08763","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":"2026-07-05T11:20:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zToLOcuHQRCLqGpnqYWjCrT8ntutnTY+VAzvvk1eREUQdw/00tzyOzsodQ428r+cbh6fHKFw5iSKVyzMgiCcAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:00:08.286116Z"},"content_sha256":"635d6002a89bc3e9a6de5b2bead0bbda170dc97ae66d5a6c3f50b972d24a79f6","schema_version":"1.0","event_id":"sha256:635d6002a89bc3e9a6de5b2bead0bbda170dc97ae66d5a6c3f50b972d24a79f6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GRHFK3LN3K42MOZHFRXYX5IGL2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Few-Shot Learner Generalizes Across AI-Generated Image Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jing Li, Jing Liu, Shiyu Wu, Yequan Wang","submitted_at":"2025-01-15T12:33:11Z","abstract_excerpt":"Current fake image detectors trained on large synthetic image datasets perform satisfactorily on limited studied generative models. However, these detectors suffer a notable performance decline over unseen models. Besides, collecting adequate training data from online generative models is often expensive or infeasible. To overcome these issues, we propose Few-Shot Detector (FSD), a novel AI-generated image detector which learns a specialized metric space for effectively distinguishing unseen fake images using very few samples. Experiments show that FSD achieves state-of-the-art performance by "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.08763","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/2501.08763/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":"2026-07-05T11:20:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hbb9sm2Ser3oe4CiYiBHfKUk3k+x/6dfKMCzNh1rbNVUhxFd2FaMDMz9vAfeJKKQ0QmPatYc94WFWwquN4SbDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:00:08.288047Z"},"content_sha256":"d8952166b251092c38430925f7d575999280106b7ae1a38837bb0d29238e62bc","schema_version":"1.0","event_id":"sha256:d8952166b251092c38430925f7d575999280106b7ae1a38837bb0d29238e62bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/bundle.json","state_url":"https://pith.science/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/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":"2026-08-10T10:00:08Z","links":{"resolver":"https://pith.science/pith/GRHFK3LN3K42MOZHFRXYX5IGL2","bundle":"https://pith.science/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/bundle.json","state":"https://pith.science/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GRHFK3LN3K42MOZHFRXYX5IGL2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GRHFK3LN3K42MOZHFRXYX5IGL2","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":"72d8c15a061f8f8c137ef06e7932e91577cf9924efacb42bcab485c28567db36","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T12:33:11Z","title_canon_sha256":"ae7e35e49a152d1c5e67b1d61cc16710fd832eba89544974d7277de7bc3fb837"},"schema_version":"1.0","source":{"id":"2501.08763","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.08763","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"arxiv_version","alias_value":"2501.08763v2","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.08763","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_12","alias_value":"GRHFK3LN3K42","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_16","alias_value":"GRHFK3LN3K42MOZH","created_at":"2026-07-05T11:20:08Z"},{"alias_kind":"pith_short_8","alias_value":"GRHFK3LN","created_at":"2026-07-05T11:20:08Z"}],"graph_snapshots":[{"event_id":"sha256:d8952166b251092c38430925f7d575999280106b7ae1a38837bb0d29238e62bc","target":"graph","created_at":"2026-07-05T11:20:08Z","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/2501.08763/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current fake image detectors trained on large synthetic image datasets perform satisfactorily on limited studied generative models. However, these detectors suffer a notable performance decline over unseen models. Besides, collecting adequate training data from online generative models is often expensive or infeasible. To overcome these issues, we propose Few-Shot Detector (FSD), a novel AI-generated image detector which learns a specialized metric space for effectively distinguishing unseen fake images using very few samples. Experiments show that FSD achieves state-of-the-art performance by ","authors_text":"Jing Li, Jing Liu, Shiyu Wu, Yequan Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T12:33:11Z","title":"Few-Shot Learner Generalizes Across AI-Generated Image Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.08763","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":"sha256:635d6002a89bc3e9a6de5b2bead0bbda170dc97ae66d5a6c3f50b972d24a79f6","target":"record","created_at":"2026-07-05T11:20:08Z","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":"72d8c15a061f8f8c137ef06e7932e91577cf9924efacb42bcab485c28567db36","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T12:33:11Z","title_canon_sha256":"ae7e35e49a152d1c5e67b1d61cc16710fd832eba89544974d7277de7bc3fb837"},"schema_version":"1.0","source":{"id":"2501.08763","kind":"arxiv","version":2}},"canonical_sha256":"344e556d6ddab9a63b272c6f8bf5065e8a4707256e7d104e1ce8fd0d22fa446d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"344e556d6ddab9a63b272c6f8bf5065e8a4707256e7d104e1ce8fd0d22fa446d","first_computed_at":"2026-07-05T11:20:08.011449Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:08.011449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UEoeITjyDBOavdNwb5+lW9vyasXQPxIGa1agiQxx0Cf408H8LBmAsm9gfzrPE+Q+XbAvFhU9ur0SY+PoyJ1pDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:08.011930Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.08763","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:635d6002a89bc3e9a6de5b2bead0bbda170dc97ae66d5a6c3f50b972d24a79f6","sha256:d8952166b251092c38430925f7d575999280106b7ae1a38837bb0d29238e62bc"],"state_sha256":"11a956da7843ffe59258f30139bf27c1ddc52633a3afa61d3bb69e5bdbf8f520"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T4t2Cf7u36fwk/ruxQF6nzckGtumeH9ceKV5t/DgJSDEpujqvp/xNB21BU15TFPj7d3DZSpa+8hQyOdU729tBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T10:00:08.295384Z","bundle_sha256":"46647f9c9f74e1b0440fff6fb596080de83cf6d2fe31cec55bfad0fede1c2d40"}}