{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:ZRCNBB5HGH7NIS4J2NH6L574LO","short_pith_number":"pith:ZRCNBB5H","canonical_record":{"source":{"id":"2604.18307","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-20T14:15:57Z","cross_cats_sorted":[],"title_canon_sha256":"8d18c6e72e5bccd35b5db152d4fab639bfd8c4f4aa4d84cd7dfce128010fd802","abstract_canon_sha256":"83ca8370215500b3ce1ac68c7292b3ac6abe50f8eaacb268cc3149bf3916343a"},"schema_version":"1.0"},"canonical_sha256":"cc44d087a731fed44b89d34fe5f7fc5ba2a5dbe2bf287fe10cdf63c92f534354","source":{"kind":"arxiv","id":"2604.18307","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.18307","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"arxiv_version","alias_value":"2604.18307v2","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.18307","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZRCNBB5HGH7N","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZRCNBB5HGH7NIS4J","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZRCNBB5H","created_at":"2026-06-12T01:09:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:ZRCNBB5HGH7NIS4J2NH6L574LO","target":"record","payload":{"canonical_record":{"source":{"id":"2604.18307","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-20T14:15:57Z","cross_cats_sorted":[],"title_canon_sha256":"8d18c6e72e5bccd35b5db152d4fab639bfd8c4f4aa4d84cd7dfce128010fd802","abstract_canon_sha256":"83ca8370215500b3ce1ac68c7292b3ac6abe50f8eaacb268cc3149bf3916343a"},"schema_version":"1.0"},"canonical_sha256":"cc44d087a731fed44b89d34fe5f7fc5ba2a5dbe2bf287fe10cdf63c92f534354","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:09:27.923352Z","signature_b64":"afwZeuUXwo0e208seF9tN88Nr/2j9XErbCdBHmax1tv6kOtaERRG0kxYnzjxksS+k7+IGwtSpFol0L0IGqOZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc44d087a731fed44b89d34fe5f7fc5ba2a5dbe2bf287fe10cdf63c92f534354","last_reissued_at":"2026-06-12T01:09:27.922660Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:09:27.922660Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.18307","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":"2026-06-12T01:09:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i4HmljuNyf1DxWTKW88CYCYKy9DCj7nj0Jf3Ww2EjREKIY3L342tBibb9i6y5IH6HdQ0tL0UgQO2rJ8LY0kPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:12:31.343523Z"},"content_sha256":"961940e9f67827e06ea16a83ce6f137334ea0a18cbe53fbbeb5dceab4b0b5384","schema_version":"1.0","event_id":"sha256:961940e9f67827e06ea16a83ce6f137334ea0a18cbe53fbbeb5dceab4b0b5384"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:ZRCNBB5HGH7NIS4J2NH6L574LO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reasoning Models Know What's Important, and Encode It in Their Activations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps.","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jonathan Rosenfeld, Martin Tutek, Tomer Ashuach, Yaniv Nikankin, Yonatan Belinkov","submitted_at":"2026-04-20T14:15:57Z","abstract_excerpt":"Language models often solve complex tasks by generating long reasoning chains, consisting of many steps with varying importance. While some steps are crucial for generating the final answer, others are removable. Determining which steps matter most, and why, remains an open question central to understanding how models process reasoning. We investigate if this question is best approached through model internals or through tokens of the reasoning chain itself. We find that model activations contain more information than tokens for identifying important reasoning steps. Crucially, by training pro"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"by training probes on model activations to predict importance, we show that models encode an internal representation of step importance, even prior to the generation of subsequent steps. This internal representation of importance generalizes across models, is distributed across layers, and does not correlate with surface-level features.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That operational definitions of step importance (e.g., via removability) used to train the probes accurately reflect the causal importance within the model's reasoning process rather than spurious correlations.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Reasoning models internally represent step importance in activations prior to generation, detectable via probes and independent of token-level features.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"ce709eb4a60a7c658e2442ffd65f5d2e2470bc7977cdaa6b18e408d6cae2ec28"},"source":{"id":"2604.18307","kind":"arxiv","version":2},"verdict":{"id":"bab1237e-dde0-4852-bf1d-703018e169dd","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-10T05:22:18.243687Z","strongest_claim":"by training probes on model activations to predict importance, we show that models encode an internal representation of step importance, even prior to the generation of subsequent steps. This internal representation of importance generalizes across models, is distributed across layers, and does not correlate with surface-level features.","one_line_summary":"Reasoning models internally represent step importance in activations prior to generation, detectable via probes and independent of token-level features.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That operational definitions of step importance (e.g., via removability) used to train the probes accurately reflect the causal importance within the model's reasoning process rather than spurious correlations.","pith_extraction_headline":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps."},"integrity":{"clean":false,"summary":{"advisory":1,"critical":0,"by_detector":{"doi_compliance":{"total":1,"advisory":1,"critical":0,"informational":0}},"informational":0},"endpoint":"/pith/2604.18307/integrity.json","findings":[{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish) was visible in the surrounding text but could not be confirmed against doi.org as printed.","detector":"doi_compliance","severity":"advisory","ref_index":1,"audited_at":"2026-05-20T04:11:48.303543Z","detected_doi":"10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish","finding_type":"recoverable_identifier","verdict_class":"incontrovertible","detected_arxiv_id":null}],"available":true,"detectors_run":[{"name":"doi_compliance","ran_at":"2026-05-20T04:11:48.303543Z","status":"completed","version":"1.0.0","findings_count":1}],"snapshot_sha256":"8c06fdae7287c606dc7d3422f7d8a31223b39a5b07e56788ca801291291a5c9d"},"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":"bab1237e-dde0-4852-bf1d-703018e169dd"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-12T01:09:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S0U7nOLAdxQBlc/9X20brXdfxqd3FWQShpXKogOQgZcc5k+h/+ILcc4oI9vi5RqiLA6Zxozs9RMvj6B+B/BWCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:12:31.344825Z"},"content_sha256":"7e1e4b2bec2c908a7f96b6ed1cfb8b975a081ca19adc638ce27ed1f365cbf83f","schema_version":"1.0","event_id":"sha256:7e1e4b2bec2c908a7f96b6ed1cfb8b975a081ca19adc638ce27ed1f365cbf83f"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZRCNBB5HGH7NIS4J2NH6L574LO","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"URLhttps://aclanthology.org/2024.acl-long.254/. Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al. Openai o1 system card. arXiv preprint arXiv:24","arxiv_id":"2604.18307","detector":"doi_compliance","evidence":{"ref_index":1,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"URLhttps://aclanthology.org/2024.acl-long.254/. Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al. Openai o1 system card. arXiv preprint arXiv:24","reconstructed_doi":"10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish"},"severity":"advisory","ref_index":1,"audited_at":"2026-05-20T04:11:48.303543Z","event_type":"pith.integrity.v1","detected_doi":"10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"5e539e628090cbce3693cd1323a3dbca59dc20dd23700946a453ebc47df8ac31","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":4731,"payload_sha256":"3f81c1e71a2bf41e762687310fca9c83a4f7a42b135b76304fbcd7d1ab87c716","signature_b64":"MUUGjj+uIsYsIdGT9H3ix4ycImnavEy5HbVF67ULgJiZcinumNcj1gydQLWvrWumsC/U6IkxrBg4egyYGb7ACQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T04:12:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4SpPDbEONusCeHinKm25Z26DfwBN+CvTYASDy4MoqsX3pO5SjQattx8uJk9Tw6lCEbR1T8aA9NotzBro+o3DBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:12:31.431563Z"},"content_sha256":"2fc9cd24b1322f0b79a44ca95a68cc134c0bfbb1ad2fa52a4e96c8bce2a99a0c","schema_version":"1.0","event_id":"sha256:2fc9cd24b1322f0b79a44ca95a68cc134c0bfbb1ad2fa52a4e96c8bce2a99a0c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/bundle.json","state_url":"https://pith.science/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/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":"2026-08-03T18:12:31Z","links":{"resolver":"https://pith.science/pith/ZRCNBB5HGH7NIS4J2NH6L574LO","bundle":"https://pith.science/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/bundle.json","state":"https://pith.science/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZRCNBB5HGH7NIS4J2NH6L574LO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZRCNBB5HGH7NIS4J2NH6L574LO","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"83ca8370215500b3ce1ac68c7292b3ac6abe50f8eaacb268cc3149bf3916343a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-20T14:15:57Z","title_canon_sha256":"8d18c6e72e5bccd35b5db152d4fab639bfd8c4f4aa4d84cd7dfce128010fd802"},"schema_version":"1.0","source":{"id":"2604.18307","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.18307","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"arxiv_version","alias_value":"2604.18307v2","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.18307","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZRCNBB5HGH7N","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZRCNBB5HGH7NIS4J","created_at":"2026-06-12T01:09:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZRCNBB5H","created_at":"2026-06-12T01:09:27Z"}],"graph_snapshots":[{"event_id":"sha256:7e1e4b2bec2c908a7f96b6ed1cfb8b975a081ca19adc638ce27ed1f365cbf83f","target":"graph","created_at":"2026-06-12T01:09:27Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"by training probes on model activations to predict importance, we show that models encode an internal representation of step importance, even prior to the generation of subsequent steps. This internal representation of importance generalizes across models, is distributed across layers, and does not correlate with surface-level features."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That operational definitions of step importance (e.g., via removability) used to train the probes accurately reflect the causal importance within the model's reasoning process rather than spurious correlations."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"Reasoning models internally represent step importance in activations prior to generation, detectable via probes and independent of token-level features."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps."}],"snapshot_sha256":"ce709eb4a60a7c658e2442ffd65f5d2e2470bc7977cdaa6b18e408d6cae2ec28"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":false,"detectors_run":[{"findings_count":1,"name":"doi_compliance","ran_at":"2026-05-20T04:11:48.303543Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2604.18307/integrity.json","findings":[{"audited_at":"2026-05-20T04:11:48.303543Z","detected_arxiv_id":null,"detected_doi":"10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish","detector":"doi_compliance","finding_type":"recoverable_identifier","note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.18653/v1/2025.emnlp-main.329.URLhttps://aclanthology.org/2025.emnlp-main.329/.Nitish) was visible in the surrounding text but could not be confirmed against doi.org as printed.","ref_index":1,"severity":"advisory","verdict_class":"incontrovertible"}],"snapshot_sha256":"8c06fdae7287c606dc7d3422f7d8a31223b39a5b07e56788ca801291291a5c9d","summary":{"advisory":1,"by_detector":{"doi_compliance":{"advisory":1,"critical":0,"informational":0,"total":1}},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Language models often solve complex tasks by generating long reasoning chains, consisting of many steps with varying importance. While some steps are crucial for generating the final answer, others are removable. Determining which steps matter most, and why, remains an open question central to understanding how models process reasoning. We investigate if this question is best approached through model internals or through tokens of the reasoning chain itself. We find that model activations contain more information than tokens for identifying important reasoning steps. Crucially, by training pro","authors_text":"Jonathan Rosenfeld, Martin Tutek, Tomer Ashuach, Yaniv Nikankin, Yonatan Belinkov","cross_cats":[],"headline":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-20T14:15:57Z","title":"Reasoning Models Know What's Important, and Encode It in Their Activations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.18307","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-10T05:22:18.243687Z","id":"bab1237e-dde0-4852-bf1d-703018e169dd","model_set":{"reader":"grok-4.3"},"one_line_summary":"Reasoning models internally represent step importance in activations prior to generation, detectable via probes and independent of token-level features.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Language models encode an internal representation of reasoning step importance in their activations prior to generating subsequent steps.","strongest_claim":"by training probes on model activations to predict importance, we show that models encode an internal representation of step importance, even prior to the generation of subsequent steps. This internal representation of importance generalizes across models, is distributed across layers, and does not correlate with surface-level features.","weakest_assumption":"That operational definitions of step importance (e.g., via removability) used to train the probes accurately reflect the causal importance within the model's reasoning process rather than spurious correlations."}},"verdict_id":"bab1237e-dde0-4852-bf1d-703018e169dd"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:961940e9f67827e06ea16a83ce6f137334ea0a18cbe53fbbeb5dceab4b0b5384","target":"record","created_at":"2026-06-12T01:09:27Z","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":"83ca8370215500b3ce1ac68c7292b3ac6abe50f8eaacb268cc3149bf3916343a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-20T14:15:57Z","title_canon_sha256":"8d18c6e72e5bccd35b5db152d4fab639bfd8c4f4aa4d84cd7dfce128010fd802"},"schema_version":"1.0","source":{"id":"2604.18307","kind":"arxiv","version":2}},"canonical_sha256":"cc44d087a731fed44b89d34fe5f7fc5ba2a5dbe2bf287fe10cdf63c92f534354","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc44d087a731fed44b89d34fe5f7fc5ba2a5dbe2bf287fe10cdf63c92f534354","first_computed_at":"2026-06-12T01:09:27.922660Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-12T01:09:27.922660Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"afwZeuUXwo0e208seF9tN88Nr/2j9XErbCdBHmax1tv6kOtaERRG0kxYnzjxksS+k7+IGwtSpFol0L0IGqOZDw==","signature_status":"signed_v1","signed_at":"2026-06-12T01:09:27.923352Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.18307","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2fc9cd24b1322f0b79a44ca95a68cc134c0bfbb1ad2fa52a4e96c8bce2a99a0c","sha256:961940e9f67827e06ea16a83ce6f137334ea0a18cbe53fbbeb5dceab4b0b5384","sha256:7e1e4b2bec2c908a7f96b6ed1cfb8b975a081ca19adc638ce27ed1f365cbf83f"],"state_sha256":"59dedd9fc884c7c73b68a69049fe46e0cc9e661ea77a416e668f72567a331bb8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nvrmOj/eshK7ZIllcn9sAk5XBgterQNxNYXH1adoSekm8a3DAffPkOgvpnwV8beDo8bi3A2zNAfLrRkZkW3lBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T18:12:31.437888Z","bundle_sha256":"0ddb1dbfb69a19cc474de54741582653b2405fbe0db8bb696f4e7b157fc2da37"}}