{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CJZ6E7TTOUEYBVQNEUNIIQJAAW","short_pith_number":"pith:CJZ6E7TT","canonical_record":{"source":{"id":"2405.15268","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-24T06:51:38Z","cross_cats_sorted":[],"title_canon_sha256":"9d26f9b943d8c81bc07a1fadbec39253839693825131ff408b5a0bc7d6026efb","abstract_canon_sha256":"26e943312922daa53c2c1afb9f105450f99a5d57eb7c46ede3b1b5b536ae8b09"},"schema_version":"1.0"},"canonical_sha256":"1273e27e73750980d60d251a84412005a79a24cdf84687d409802531a0b83130","source":{"kind":"arxiv","id":"2405.15268","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.15268","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"arxiv_version","alias_value":"2405.15268v3","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.15268","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_12","alias_value":"CJZ6E7TTOUEY","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_16","alias_value":"CJZ6E7TTOUEYBVQN","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_8","alias_value":"CJZ6E7TT","created_at":"2026-07-05T08:27:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CJZ6E7TTOUEYBVQNEUNIIQJAAW","target":"record","payload":{"canonical_record":{"source":{"id":"2405.15268","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-24T06:51:38Z","cross_cats_sorted":[],"title_canon_sha256":"9d26f9b943d8c81bc07a1fadbec39253839693825131ff408b5a0bc7d6026efb","abstract_canon_sha256":"26e943312922daa53c2c1afb9f105450f99a5d57eb7c46ede3b1b5b536ae8b09"},"schema_version":"1.0"},"canonical_sha256":"1273e27e73750980d60d251a84412005a79a24cdf84687d409802531a0b83130","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:48.974586Z","signature_b64":"dxj2NQj1VgC08WpaHloWd4fksFYSbAK5fo9aq7K4mDFWdgCVXd2blhxEjqAqY4hnh96y+bBqK8SLXvINVwBnCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1273e27e73750980d60d251a84412005a79a24cdf84687d409802531a0b83130","last_reissued_at":"2026-07-05T08:27:48.974039Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:48.974039Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.15268","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:27:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N1qS23lNiKWjdDiNUbfZuJjKw5Oo+jsSswGzxMuziblU8b8RmVuIgi6s9WhuWFqYocwy07CDGaFscVOdLoH0Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:36:45.999278Z"},"content_sha256":"778e8e538288ec1ba6490d96b419f354ffeed26c9c93f6308cc618ec67639312","schema_version":"1.0","event_id":"sha256:778e8e538288ec1ba6490d96b419f354ffeed26c9c93f6308cc618ec67639312"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CJZ6E7TTOUEYBVQNEUNIIQJAAW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hui Chen, Jin Li, Longbing Cao, Xuhui Fan, Zhangkai Wu, Zhilin Zhao","submitted_at":"2024-05-24T06:51:38Z","abstract_excerpt":"The recently proposed Bayesian Flow Networks~(BFNs) show great potential in modeling parameter spaces, offering a unified strategy for handling continuous, discretized, and discrete data. However, BFNs cannot learn high-level semantic representation from the parameter space since {common encoders, which encode data into one static representation, cannot capture semantic changes in parameters.} This motivates a new direction: learning semantic representations hidden in the parameter spaces to characterize mixed-typed noisy data. {Accordingly, we propose a representation learning framework named"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.15268","kind":"arxiv","version":3},"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/2405.15268/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":"2026-07-05T08:27:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zWkT4IC5az0KHS6J91cjdY4jM7KGuKZkYgGocUs+uIe9nrORp2WWhm5dho0HKMcaWt1fe76wjGhU1cSSX9iZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:36:45.999789Z"},"content_sha256":"03d15c749380a502617a51462c2524ebad3dda5c02d14be5f0ade1b2ac28fc33","schema_version":"1.0","event_id":"sha256:03d15c749380a502617a51462c2524ebad3dda5c02d14be5f0ade1b2ac28fc33"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/bundle.json","state_url":"https://pith.science/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/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":"2026-08-09T01:36:46Z","links":{"resolver":"https://pith.science/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW","bundle":"https://pith.science/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/bundle.json","state":"https://pith.science/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CJZ6E7TTOUEYBVQNEUNIIQJAAW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CJZ6E7TTOUEYBVQNEUNIIQJAAW","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":"26e943312922daa53c2c1afb9f105450f99a5d57eb7c46ede3b1b5b536ae8b09","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-24T06:51:38Z","title_canon_sha256":"9d26f9b943d8c81bc07a1fadbec39253839693825131ff408b5a0bc7d6026efb"},"schema_version":"1.0","source":{"id":"2405.15268","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.15268","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"arxiv_version","alias_value":"2405.15268v3","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.15268","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_12","alias_value":"CJZ6E7TTOUEY","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_16","alias_value":"CJZ6E7TTOUEYBVQN","created_at":"2026-07-05T08:27:48Z"},{"alias_kind":"pith_short_8","alias_value":"CJZ6E7TT","created_at":"2026-07-05T08:27:48Z"}],"graph_snapshots":[{"event_id":"sha256:03d15c749380a502617a51462c2524ebad3dda5c02d14be5f0ade1b2ac28fc33","target":"graph","created_at":"2026-07-05T08:27:48Z","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/2405.15268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The recently proposed Bayesian Flow Networks~(BFNs) show great potential in modeling parameter spaces, offering a unified strategy for handling continuous, discretized, and discrete data. However, BFNs cannot learn high-level semantic representation from the parameter space since {common encoders, which encode data into one static representation, cannot capture semantic changes in parameters.} This motivates a new direction: learning semantic representations hidden in the parameter spaces to characterize mixed-typed noisy data. {Accordingly, we propose a representation learning framework named","authors_text":"Hui Chen, Jin Li, Longbing Cao, Xuhui Fan, Zhangkai Wu, Zhilin Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-24T06:51:38Z","title":"ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.15268","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":"sha256:778e8e538288ec1ba6490d96b419f354ffeed26c9c93f6308cc618ec67639312","target":"record","created_at":"2026-07-05T08:27:48Z","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":"26e943312922daa53c2c1afb9f105450f99a5d57eb7c46ede3b1b5b536ae8b09","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-24T06:51:38Z","title_canon_sha256":"9d26f9b943d8c81bc07a1fadbec39253839693825131ff408b5a0bc7d6026efb"},"schema_version":"1.0","source":{"id":"2405.15268","kind":"arxiv","version":3}},"canonical_sha256":"1273e27e73750980d60d251a84412005a79a24cdf84687d409802531a0b83130","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1273e27e73750980d60d251a84412005a79a24cdf84687d409802531a0b83130","first_computed_at":"2026-07-05T08:27:48.974039Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:27:48.974039Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dxj2NQj1VgC08WpaHloWd4fksFYSbAK5fo9aq7K4mDFWdgCVXd2blhxEjqAqY4hnh96y+bBqK8SLXvINVwBnCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:27:48.974586Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.15268","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:778e8e538288ec1ba6490d96b419f354ffeed26c9c93f6308cc618ec67639312","sha256:03d15c749380a502617a51462c2524ebad3dda5c02d14be5f0ade1b2ac28fc33"],"state_sha256":"1279e5ddb27b1d3c01e2a0dff1281f60fc8e71e9c0d0aaf979fd6c1513d10739"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IzZyL8Ka6oQDVT39OTC4XJn2JUz/imfCZdKPGNkZwhL7AU0qK19K4zIqILS8gbkXcESJrHc+O1Y1msGY2f6HAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T01:36:46.005222Z","bundle_sha256":"ce48bc08a6989b4d1c1ba8a028ac4ef39cd8fe13b7db9fb1b635afea222e9ab3"}}