{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3R7M2H47ZLD72KZAX7FBW6MF3V","short_pith_number":"pith:3R7M2H47","canonical_record":{"source":{"id":"2606.09912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-06T12:10:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"258a01d0ce3039794c97b52b1df5f08ddcbe3391c2df054dafbfd3e46aa98b95","abstract_canon_sha256":"51c7e7eace2f5b8274782fa99d4481aa2d233243bd1b6b46387312706fad273d"},"schema_version":"1.0"},"canonical_sha256":"dc7ecd1f9fcac7fd2b20bfca1b7985dd79416a9e9949af149d8e189e2589a789","source":{"kind":"arxiv","id":"2606.09912","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09912","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09912v1","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09912","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_12","alias_value":"3R7M2H47ZLD7","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_16","alias_value":"3R7M2H47ZLD72KZA","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_8","alias_value":"3R7M2H47","created_at":"2026-06-10T00:08:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3R7M2H47ZLD72KZAX7FBW6MF3V","target":"record","payload":{"canonical_record":{"source":{"id":"2606.09912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-06T12:10:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"258a01d0ce3039794c97b52b1df5f08ddcbe3391c2df054dafbfd3e46aa98b95","abstract_canon_sha256":"51c7e7eace2f5b8274782fa99d4481aa2d233243bd1b6b46387312706fad273d"},"schema_version":"1.0"},"canonical_sha256":"dc7ecd1f9fcac7fd2b20bfca1b7985dd79416a9e9949af149d8e189e2589a789","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T00:08:32.710523Z","signature_b64":"xJ0DC0VliZnEAS1jLnYN4NOQxrAyEM26IWogEKPhREk+RGE0/MN+u1kDbHom3C2QL+w2E9CFlX0qFSDrC1eVAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc7ecd1f9fcac7fd2b20bfca1b7985dd79416a9e9949af149d8e189e2589a789","last_reissued_at":"2026-06-10T00:08:32.709490Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T00:08:32.709490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.09912","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-10T00:08:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1FBOXI1eRJmvg8Rwc+ZZhwpbxNNgKMCgIwqnFUuNdxRhqi/ez1jM1v85QN4RcnSY23qrV39G+S2/WrV/dkGLBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T14:32:27.100758Z"},"content_sha256":"d0d391fbebb05f5c47ac1318808dacddfa6209cbe29876c62d64788f53457ef7","schema_version":"1.0","event_id":"sha256:d0d391fbebb05f5c47ac1318808dacddfa6209cbe29876c62d64788f53457ef7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3R7M2H47ZLD72KZAX7FBW6MF3V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Aaryan Nagpal, Debdeep Sanyal, Dhruv Kumar, Murari Mandal, Saurabh Deshpande","submitted_at":"2026-06-06T12:10:38Z","abstract_excerpt":"Choosing the wrong synthetic generator for time-series foundation model pretraining is costly: under identical training budgets, the best and worst generators produce up to a $2\\times$ gap in forecasting error, yet the field has no principled way to make this choice. The problem is compounded by the fact that generator rankings are not stable across architectures: across 11 generator families evaluated on Chronos-T5-Mini and Moirai-Small trained from scratch, we find that which generators are useful depends on the model architecture. Rather than solving the generator selection problem, we side"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09912","kind":"arxiv","version":1},"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/2606.09912/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":"2026-06-10T00:08:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FEQq8qM26Hgf733GVxOZQX0CR1qXKzf1R0lnVlq41sxet53PNdVUK4tE5agW39hGnNIMNBcxVW9GurRh07pDAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T14:32:27.101200Z"},"content_sha256":"01a0340ae76d53a621eb8dfa9e417184ea4e00f4eaad939ddfb9025e470b7e31","schema_version":"1.0","event_id":"sha256:01a0340ae76d53a621eb8dfa9e417184ea4e00f4eaad939ddfb9025e470b7e31"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/bundle.json","state_url":"https://pith.science/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/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":"2026-06-29T14:32:27Z","links":{"resolver":"https://pith.science/pith/3R7M2H47ZLD72KZAX7FBW6MF3V","bundle":"https://pith.science/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/bundle.json","state":"https://pith.science/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3R7M2H47ZLD72KZAX7FBW6MF3V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3R7M2H47ZLD72KZAX7FBW6MF3V","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":"51c7e7eace2f5b8274782fa99d4481aa2d233243bd1b6b46387312706fad273d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-06T12:10:38Z","title_canon_sha256":"258a01d0ce3039794c97b52b1df5f08ddcbe3391c2df054dafbfd3e46aa98b95"},"schema_version":"1.0","source":{"id":"2606.09912","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09912","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09912v1","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09912","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_12","alias_value":"3R7M2H47ZLD7","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_16","alias_value":"3R7M2H47ZLD72KZA","created_at":"2026-06-10T00:08:32Z"},{"alias_kind":"pith_short_8","alias_value":"3R7M2H47","created_at":"2026-06-10T00:08:32Z"}],"graph_snapshots":[{"event_id":"sha256:01a0340ae76d53a621eb8dfa9e417184ea4e00f4eaad939ddfb9025e470b7e31","target":"graph","created_at":"2026-06-10T00:08:32Z","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/2606.09912/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Choosing the wrong synthetic generator for time-series foundation model pretraining is costly: under identical training budgets, the best and worst generators produce up to a $2\\times$ gap in forecasting error, yet the field has no principled way to make this choice. The problem is compounded by the fact that generator rankings are not stable across architectures: across 11 generator families evaluated on Chronos-T5-Mini and Moirai-Small trained from scratch, we find that which generators are useful depends on the model architecture. Rather than solving the generator selection problem, we side","authors_text":"Aaryan Nagpal, Debdeep Sanyal, Dhruv Kumar, Murari Mandal, Saurabh Deshpande","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-06T12:10:38Z","title":"Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09912","kind":"arxiv","version":1},"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:d0d391fbebb05f5c47ac1318808dacddfa6209cbe29876c62d64788f53457ef7","target":"record","created_at":"2026-06-10T00:08:32Z","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":"51c7e7eace2f5b8274782fa99d4481aa2d233243bd1b6b46387312706fad273d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-06T12:10:38Z","title_canon_sha256":"258a01d0ce3039794c97b52b1df5f08ddcbe3391c2df054dafbfd3e46aa98b95"},"schema_version":"1.0","source":{"id":"2606.09912","kind":"arxiv","version":1}},"canonical_sha256":"dc7ecd1f9fcac7fd2b20bfca1b7985dd79416a9e9949af149d8e189e2589a789","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc7ecd1f9fcac7fd2b20bfca1b7985dd79416a9e9949af149d8e189e2589a789","first_computed_at":"2026-06-10T00:08:32.709490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T00:08:32.709490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xJ0DC0VliZnEAS1jLnYN4NOQxrAyEM26IWogEKPhREk+RGE0/MN+u1kDbHom3C2QL+w2E9CFlX0qFSDrC1eVAQ==","signature_status":"signed_v1","signed_at":"2026-06-10T00:08:32.710523Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.09912","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0d391fbebb05f5c47ac1318808dacddfa6209cbe29876c62d64788f53457ef7","sha256:01a0340ae76d53a621eb8dfa9e417184ea4e00f4eaad939ddfb9025e470b7e31"],"state_sha256":"45b9763fdaedad58653a71737fafeaa742bcfd556497682ec9b4d4c0289712e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M2Ng5ILC0lzn68UQrCxSs6uxmycX03RQ0d65D9wXOFNZW5WyZBGHOZbY7wCyE3R3nkAnxQ19UdXqke2PA9h/DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T14:32:27.103637Z","bundle_sha256":"7b024fd808a8c60e9394a298e93ab8223be26ce753a94183c5c38f1b30700fa9"}}