{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:BOODJYZR5K65RMINL7XIGRRGG3","short_pith_number":"pith:BOODJYZR","canonical_record":{"source":{"id":"2306.02957","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-05T15:24:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6d044cb3368456e68d06a259549939d67bf7795177080dbc7d083c414a9e8cfb","abstract_canon_sha256":"bb73b3bd61338317c9e44b573932d002a5f1049fc6834ca315dc8b0e1835d09e"},"schema_version":"1.0"},"canonical_sha256":"0b9c34e331eabdd8b10d5fee83462636fc6d97fa34ebe3f94bc39c95ab99a6c4","source":{"kind":"arxiv","id":"2306.02957","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02957","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02957v2","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02957","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_12","alias_value":"BOODJYZR5K65","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_16","alias_value":"BOODJYZR5K65RMIN","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_8","alias_value":"BOODJYZR","created_at":"2026-07-05T06:23:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:BOODJYZR5K65RMINL7XIGRRGG3","target":"record","payload":{"canonical_record":{"source":{"id":"2306.02957","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-05T15:24:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6d044cb3368456e68d06a259549939d67bf7795177080dbc7d083c414a9e8cfb","abstract_canon_sha256":"bb73b3bd61338317c9e44b573932d002a5f1049fc6834ca315dc8b0e1835d09e"},"schema_version":"1.0"},"canonical_sha256":"0b9c34e331eabdd8b10d5fee83462636fc6d97fa34ebe3f94bc39c95ab99a6c4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:23:38.284419Z","signature_b64":"x4Se5kYA9o434uED1SyFIA3CX8j6ucPtnWtiBvgvFVCPX7vRward+HZLQMODcOMQBz2viD0u91dSNeTt+Ki2Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0b9c34e331eabdd8b10d5fee83462636fc6d97fa34ebe3f94bc39c95ab99a6c4","last_reissued_at":"2026-07-05T06:23:38.283975Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:23:38.283975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.02957","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":"2026-07-05T06:23:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"laXU8b7tfmennAGfOltSvxdYDkdjQpS+NG6jFcrfG6MDOhmna6G9GFamp4fcjCBkMwDmRzYzHh3BTzEaO6eHAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:09:46.631336Z"},"content_sha256":"c343de6aa40d66dfda1c129876830190419c0da469d913fff652f9920a38e635","schema_version":"1.0","event_id":"sha256:c343de6aa40d66dfda1c129876830190419c0da469d913fff652f9920a38e635"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:BOODJYZR5K65RMINL7XIGRRGG3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alex M. Tseng, Gabriele Scalia, Nathaniel Diamant, Tommaso Biancalani","submitted_at":"2023-06-05T15:24:39Z","abstract_excerpt":"Diffusion models have achieved state-of-the-art performance in generating many different kinds of data, including images, text, and videos. Despite their success, there has been limited research on how the underlying diffusion process and the final convergent prior can affect generative performance; this research has also been limited to continuous data types and a score-based diffusion framework. To fill this gap, we explore how different discrete diffusion kernels (which converge to different prior distributions) affect the performance of diffusion models for graphs. To this end, we develope"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02957","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/2306.02957/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":"2026-07-05T06:23:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o9Ize3Bp44gw8Ff5pom+aX2tZ7hWSh6dccCCjrN91SMaG3JuEFJNcKLs39cVYlOw7SFc7YpLxQdz0423ARqyBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:09:46.631707Z"},"content_sha256":"8deeba79da25effb6997748819946fcf3f7b516f2fdbd2736b3ae458919da4a7","schema_version":"1.0","event_id":"sha256:8deeba79da25effb6997748819946fcf3f7b516f2fdbd2736b3ae458919da4a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BOODJYZR5K65RMINL7XIGRRGG3/bundle.json","state_url":"https://pith.science/pith/BOODJYZR5K65RMINL7XIGRRGG3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BOODJYZR5K65RMINL7XIGRRGG3/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":"2026-07-06T19:09:46Z","links":{"resolver":"https://pith.science/pith/BOODJYZR5K65RMINL7XIGRRGG3","bundle":"https://pith.science/pith/BOODJYZR5K65RMINL7XIGRRGG3/bundle.json","state":"https://pith.science/pith/BOODJYZR5K65RMINL7XIGRRGG3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BOODJYZR5K65RMINL7XIGRRGG3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:BOODJYZR5K65RMINL7XIGRRGG3","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":"bb73b3bd61338317c9e44b573932d002a5f1049fc6834ca315dc8b0e1835d09e","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-05T15:24:39Z","title_canon_sha256":"6d044cb3368456e68d06a259549939d67bf7795177080dbc7d083c414a9e8cfb"},"schema_version":"1.0","source":{"id":"2306.02957","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02957","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02957v2","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02957","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_12","alias_value":"BOODJYZR5K65","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_16","alias_value":"BOODJYZR5K65RMIN","created_at":"2026-07-05T06:23:38Z"},{"alias_kind":"pith_short_8","alias_value":"BOODJYZR","created_at":"2026-07-05T06:23:38Z"}],"graph_snapshots":[{"event_id":"sha256:8deeba79da25effb6997748819946fcf3f7b516f2fdbd2736b3ae458919da4a7","target":"graph","created_at":"2026-07-05T06:23:38Z","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/2306.02957/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have achieved state-of-the-art performance in generating many different kinds of data, including images, text, and videos. Despite their success, there has been limited research on how the underlying diffusion process and the final convergent prior can affect generative performance; this research has also been limited to continuous data types and a score-based diffusion framework. To fill this gap, we explore how different discrete diffusion kernels (which converge to different prior distributions) affect the performance of diffusion models for graphs. To this end, we develope","authors_text":"Alex M. Tseng, Gabriele Scalia, Nathaniel Diamant, Tommaso Biancalani","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-05T15:24:39Z","title":"Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02957","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:c343de6aa40d66dfda1c129876830190419c0da469d913fff652f9920a38e635","target":"record","created_at":"2026-07-05T06:23:38Z","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":"bb73b3bd61338317c9e44b573932d002a5f1049fc6834ca315dc8b0e1835d09e","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-05T15:24:39Z","title_canon_sha256":"6d044cb3368456e68d06a259549939d67bf7795177080dbc7d083c414a9e8cfb"},"schema_version":"1.0","source":{"id":"2306.02957","kind":"arxiv","version":2}},"canonical_sha256":"0b9c34e331eabdd8b10d5fee83462636fc6d97fa34ebe3f94bc39c95ab99a6c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b9c34e331eabdd8b10d5fee83462636fc6d97fa34ebe3f94bc39c95ab99a6c4","first_computed_at":"2026-07-05T06:23:38.283975Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:23:38.283975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x4Se5kYA9o434uED1SyFIA3CX8j6ucPtnWtiBvgvFVCPX7vRward+HZLQMODcOMQBz2viD0u91dSNeTt+Ki2Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:23:38.284419Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.02957","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c343de6aa40d66dfda1c129876830190419c0da469d913fff652f9920a38e635","sha256:8deeba79da25effb6997748819946fcf3f7b516f2fdbd2736b3ae458919da4a7"],"state_sha256":"586708dab112a2ff6b52d2e1ea85186c8bd31e13811c06b2fc1330d39534263e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BApS+LhFul3S+rXJKm58CAEwj+jDhZyx/eSKY3BHWwfna9ZSPujdbazy2vOKAfRRdi6+I9v/N8+cqLPtype3Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T19:09:46.633936Z","bundle_sha256":"ebb94e80e3d3cf0ea7826ca6822473d5f46a1f9b1470096d070176aaad55f982"}}