{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:EWPC7NK3VWTC66K7S4SE736S35","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":"3ead2e3478360afb70e627562597f519ac03320fd12dc0d2ca4f8cd327355494","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T17:59:14Z","title_canon_sha256":"b46d6ac7b5eed274ce5ad7d0f7479bb7401582b5d322b692ba3d5bd89ed05ce9"},"schema_version":"1.0","source":{"id":"2304.02012","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.02012","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"arxiv_version","alias_value":"2304.02012v3","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.02012","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_12","alias_value":"EWPC7NK3VWTC","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_16","alias_value":"EWPC7NK3VWTC66K7","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_8","alias_value":"EWPC7NK3","created_at":"2026-07-05T06:00:37Z"}],"graph_snapshots":[{"event_id":"sha256:0fcff421cb41cca8b17434f147924320d3dd536d67ca0d2d993fc35a44a16d7f","target":"graph","created_at":"2026-07-05T06:00:37Z","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/2304.02012/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning image classification and image generation using the same set of network parameters is a challenging problem. Recent advanced approaches perform well in one task often exhibit poor performance in the other. This work introduces an energy-based classifier and generator, namely EGC, which can achieve superior performance in both tasks using a single neural network. Unlike a conventional classifier that outputs a label given an image (i.e., a conditional distribution $p(y|\\mathbf{x})$), the forward pass in EGC is a classifier that outputs a joint distribution $p(\\mathbf{x},y)$, enabling a","authors_text":"Chuofan Ma, Ping Luo, Qiushan Guo, Yi Jiang, Yizhou Yu, Zehuan Yuan","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T17:59:14Z","title":"EGC: Image Generation and Classification via a Diffusion Energy-Based Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.02012","kind":"arxiv","version":3},"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:ac5f0bda1d4722309da8e347fe27ce151b64b15edba5fced385da6e3b802e5bc","target":"record","created_at":"2026-07-05T06:00:37Z","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":"3ead2e3478360afb70e627562597f519ac03320fd12dc0d2ca4f8cd327355494","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T17:59:14Z","title_canon_sha256":"b46d6ac7b5eed274ce5ad7d0f7479bb7401582b5d322b692ba3d5bd89ed05ce9"},"schema_version":"1.0","source":{"id":"2304.02012","kind":"arxiv","version":3}},"canonical_sha256":"259e2fb55bada62f795f97244fefd2df6c61f42c263fac47fd87d3f102a0768d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"259e2fb55bada62f795f97244fefd2df6c61f42c263fac47fd87d3f102a0768d","first_computed_at":"2026-07-05T06:00:37.275401Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:00:37.275401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rgGJXuITGE5FNGJ8ti59PzcBhcmtuGgIV2hUVqu01Xm3M6u10Fp74VutRsUHaXSDi7IFGLKS0VEjokiu5qOoAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:00:37.275813Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.02012","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac5f0bda1d4722309da8e347fe27ce151b64b15edba5fced385da6e3b802e5bc","sha256:0fcff421cb41cca8b17434f147924320d3dd536d67ca0d2d993fc35a44a16d7f"],"state_sha256":"893e75335abcef9bdeb8f2c058bc3e4a1506b4be008fe4afeb1f71911bc99af7"}