{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5A7THPJQBTFQQVVVEB3O4OKM7F","short_pith_number":"pith:5A7THPJQ","canonical_record":{"source":{"id":"2507.07439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-10T05:29:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fb3b629a13bd7e9327fe0e60eeda1cf04068b6bbc2bfa1d5d3a7bcdd581b3574","abstract_canon_sha256":"2589df537ac72e1f2a90137272ca1857d3b940541f1394e6387def68af1db16b"},"schema_version":"1.0"},"canonical_sha256":"e83f33bd300ccb0856b52076ee394cf97a2614d707ab7a64a5e3c900b2acc6d4","source":{"kind":"arxiv","id":"2507.07439","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.07439","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"arxiv_version","alias_value":"2507.07439v1","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.07439","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_12","alias_value":"5A7THPJQBTFQ","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_16","alias_value":"5A7THPJQBTFQQVVV","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_8","alias_value":"5A7THPJQ","created_at":"2026-07-05T11:34:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5A7THPJQBTFQQVVVEB3O4OKM7F","target":"record","payload":{"canonical_record":{"source":{"id":"2507.07439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-10T05:29:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fb3b629a13bd7e9327fe0e60eeda1cf04068b6bbc2bfa1d5d3a7bcdd581b3574","abstract_canon_sha256":"2589df537ac72e1f2a90137272ca1857d3b940541f1394e6387def68af1db16b"},"schema_version":"1.0"},"canonical_sha256":"e83f33bd300ccb0856b52076ee394cf97a2614d707ab7a64a5e3c900b2acc6d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:34:58.052226Z","signature_b64":"Sa+5/2kAg7Cr7MO6wgzQhFkJ1r7eMLIvT/s85Ci9hrB6HTtCQ8OW3LMilRj5mVwNC9bxkCAnkgki18OvZ48cBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e83f33bd300ccb0856b52076ee394cf97a2614d707ab7a64a5e3c900b2acc6d4","last_reissued_at":"2026-07-05T11:34:58.051727Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:34:58.051727Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.07439","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":"2026-07-05T11:34:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eqlvssX2XzkQhLeNrVgAwB5L7nLJdHG+JWrUUxTEmL9tsKX3cBW5F6CTiBhTLY06/pL//OguZlUbzCT9da3UAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:14:45.607749Z"},"content_sha256":"82b0d53d57fe3ea2b20e9947e8af9247f74a852ac7dd07beabdc3c3a6194af20","schema_version":"1.0","event_id":"sha256:82b0d53d57fe3ea2b20e9947e8af9247f74a852ac7dd07beabdc3c3a6194af20"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5A7THPJQBTFQQVVVEB3O4OKM7F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Interpretable Time Series Foundation Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jeremy Pawlus, Matthieu Boileau, Philippe Helluy, Svitlana Vyetrenko","submitted_at":"2025-07-10T05:29:34Z","abstract_excerpt":"In this paper, we investigate the distillation of time series reasoning capabilities into small, instruction-tuned language models as a step toward building interpretable time series foundation models. Leveraging a synthetic dataset of mean-reverting time series with systematically varied trends and noise levels, we generate natural language annotations using a large multimodal model and use these to supervise the fine-tuning of compact Qwen models. We introduce evaluation metrics that assess the quality of the distilled reasoning - focusing on trend direction, noise intensity, and extremum lo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.07439","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/2507.07439/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":"2026-07-05T11:34:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TnRBjeudKF8KmbaFx0sxxregayEUUpBRfc94W1CR6tBgkE8KkyhIaBYwjrV/umuA0yP7Dbf2skPcbpCufLDfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:14:45.608260Z"},"content_sha256":"4456747da749685cbcf36ae37e55c780fdc75407f6855c468b256a528f4f0c2b","schema_version":"1.0","event_id":"sha256:4456747da749685cbcf36ae37e55c780fdc75407f6855c468b256a528f4f0c2b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/bundle.json","state_url":"https://pith.science/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/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":"2026-08-07T06:14:45Z","links":{"resolver":"https://pith.science/pith/5A7THPJQBTFQQVVVEB3O4OKM7F","bundle":"https://pith.science/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/bundle.json","state":"https://pith.science/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5A7THPJQBTFQQVVVEB3O4OKM7F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5A7THPJQBTFQQVVVEB3O4OKM7F","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":"2589df537ac72e1f2a90137272ca1857d3b940541f1394e6387def68af1db16b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-10T05:29:34Z","title_canon_sha256":"fb3b629a13bd7e9327fe0e60eeda1cf04068b6bbc2bfa1d5d3a7bcdd581b3574"},"schema_version":"1.0","source":{"id":"2507.07439","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.07439","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"arxiv_version","alias_value":"2507.07439v1","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.07439","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_12","alias_value":"5A7THPJQBTFQ","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_16","alias_value":"5A7THPJQBTFQQVVV","created_at":"2026-07-05T11:34:58Z"},{"alias_kind":"pith_short_8","alias_value":"5A7THPJQ","created_at":"2026-07-05T11:34:58Z"}],"graph_snapshots":[{"event_id":"sha256:4456747da749685cbcf36ae37e55c780fdc75407f6855c468b256a528f4f0c2b","target":"graph","created_at":"2026-07-05T11:34:58Z","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/2507.07439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we investigate the distillation of time series reasoning capabilities into small, instruction-tuned language models as a step toward building interpretable time series foundation models. Leveraging a synthetic dataset of mean-reverting time series with systematically varied trends and noise levels, we generate natural language annotations using a large multimodal model and use these to supervise the fine-tuning of compact Qwen models. We introduce evaluation metrics that assess the quality of the distilled reasoning - focusing on trend direction, noise intensity, and extremum lo","authors_text":"Jeremy Pawlus, Matthieu Boileau, Philippe Helluy, Svitlana Vyetrenko","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-10T05:29:34Z","title":"Towards Interpretable Time Series Foundation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.07439","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":"sha256:82b0d53d57fe3ea2b20e9947e8af9247f74a852ac7dd07beabdc3c3a6194af20","target":"record","created_at":"2026-07-05T11:34:58Z","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":"2589df537ac72e1f2a90137272ca1857d3b940541f1394e6387def68af1db16b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-10T05:29:34Z","title_canon_sha256":"fb3b629a13bd7e9327fe0e60eeda1cf04068b6bbc2bfa1d5d3a7bcdd581b3574"},"schema_version":"1.0","source":{"id":"2507.07439","kind":"arxiv","version":1}},"canonical_sha256":"e83f33bd300ccb0856b52076ee394cf97a2614d707ab7a64a5e3c900b2acc6d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e83f33bd300ccb0856b52076ee394cf97a2614d707ab7a64a5e3c900b2acc6d4","first_computed_at":"2026-07-05T11:34:58.051727Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:58.051727Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sa+5/2kAg7Cr7MO6wgzQhFkJ1r7eMLIvT/s85Ci9hrB6HTtCQ8OW3LMilRj5mVwNC9bxkCAnkgki18OvZ48cBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:58.052226Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.07439","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82b0d53d57fe3ea2b20e9947e8af9247f74a852ac7dd07beabdc3c3a6194af20","sha256:4456747da749685cbcf36ae37e55c780fdc75407f6855c468b256a528f4f0c2b"],"state_sha256":"bb071663d7e88af099f4b26fb2e2b5dc5963e006d52f0c30fdf156b45a5cf472"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wx7VuQoPlRvClVlzo28mvMBPjtFlBoSN5bXNWrayu6BH8tR8VJdEXxEpkVDpLgcztAqOrGRTBdR4pZq4afDYBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T06:14:45.613809Z","bundle_sha256":"241d6a02efe2ce1612d9dee997a17cdf98792fe5aa597318629838c7d0186448"}}