{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NX5D6BUKIKJLXJ2J47DSYMGJLO","short_pith_number":"pith:NX5D6BUK","canonical_record":{"source":{"id":"2606.25439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T06:03:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"daf36e069bbccfee16c8d6809ace125044e045fced68b4a335bfa87b0b2970f9","abstract_canon_sha256":"c29e23a73a4502a91586685fe1277d99e480cc7016e9dac3b42ffa9c645c93f3"},"schema_version":"1.0"},"canonical_sha256":"6dfa3f068a4292bba749e7c72c30c95bb86761bd80af6f7544852eb981afa1f3","source":{"kind":"arxiv","id":"2606.25439","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25439","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25439v1","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25439","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_12","alias_value":"NX5D6BUKIKJL","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_16","alias_value":"NX5D6BUKIKJLXJ2J","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_8","alias_value":"NX5D6BUK","created_at":"2026-06-25T01:18:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NX5D6BUKIKJLXJ2J47DSYMGJLO","target":"record","payload":{"canonical_record":{"source":{"id":"2606.25439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T06:03:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"daf36e069bbccfee16c8d6809ace125044e045fced68b4a335bfa87b0b2970f9","abstract_canon_sha256":"c29e23a73a4502a91586685fe1277d99e480cc7016e9dac3b42ffa9c645c93f3"},"schema_version":"1.0"},"canonical_sha256":"6dfa3f068a4292bba749e7c72c30c95bb86761bd80af6f7544852eb981afa1f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:05.369376Z","signature_b64":"OxaO1oRvuhxofcHNkQb+kWA7cVGKWN38OHN7H2XuQzxtEZM3c9Pqt0q7rplcOnvZXtL6l/yORTRvOTnsOJ2oBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6dfa3f068a4292bba749e7c72c30c95bb86761bd80af6f7544852eb981afa1f3","last_reissued_at":"2026-06-25T01:18:05.368987Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:05.368987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.25439","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":"2026-06-25T01:18:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WavpHsPDoV27NHLV2TA49L1XrguokuQRIMv0PezYDAk6SRPNxoH08UsyPS5ObVT6NVmmHcXcqjtDoB/e7/I6DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T04:06:19.539500Z"},"content_sha256":"de68d876268e35f0f378b0d0b6caacf77c105a76b7e49683efc5bfdf8fcbe816","schema_version":"1.0","event_id":"sha256:de68d876268e35f0f378b0d0b6caacf77c105a76b7e49683efc5bfdf8fcbe816"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NX5D6BUKIKJLXJ2J47DSYMGJLO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TopoCast: A Topological Fidelity Framework for Evaluating Transformer-Based Time Series Forecasting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Sandareka Wickramanayake, Sandeepa Weerasekara","submitted_at":"2026-06-24T06:03:39Z","abstract_excerpt":"Deep learning-based models have achieved state-of-the-art performance in Time Series Forecasting (TSF), yet their evaluation remains dominated by pointwise error metrics such as Mean Squared Error (MSE), which quantify numerical accuracy but overlook structural properties of the forecast signal, including recurrent dynamics, oscillatory behavior, and phase alignment. As a result, forecasts exhibiting over-smoothing, phase shifts, or frequency distortions may achieve favorable error scores despite substantial structural degradation. To address this limitation, we propose TopoCast, a topology-dr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25439","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/2606.25439/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":"2026-06-25T01:18:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hgj3quwQaOyJMLffUvKF+MBO65y09yHJyQBJAEVWREObdA5YgT6cbNNCU8QoS+3PS487uIeNMIAsL+PKZ0oYBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T04:06:19.539887Z"},"content_sha256":"26ceb7e0b33605f9a48d32a99230017448c4cbe2b788f741acff11e3f9118465","schema_version":"1.0","event_id":"sha256:26ceb7e0b33605f9a48d32a99230017448c4cbe2b788f741acff11e3f9118465"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/bundle.json","state_url":"https://pith.science/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/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":"2026-06-30T04:06:19Z","links":{"resolver":"https://pith.science/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO","bundle":"https://pith.science/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/bundle.json","state":"https://pith.science/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NX5D6BUKIKJLXJ2J47DSYMGJLO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NX5D6BUKIKJLXJ2J47DSYMGJLO","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":"c29e23a73a4502a91586685fe1277d99e480cc7016e9dac3b42ffa9c645c93f3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T06:03:39Z","title_canon_sha256":"daf36e069bbccfee16c8d6809ace125044e045fced68b4a335bfa87b0b2970f9"},"schema_version":"1.0","source":{"id":"2606.25439","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25439","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25439v1","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25439","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_12","alias_value":"NX5D6BUKIKJL","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_16","alias_value":"NX5D6BUKIKJLXJ2J","created_at":"2026-06-25T01:18:05Z"},{"alias_kind":"pith_short_8","alias_value":"NX5D6BUK","created_at":"2026-06-25T01:18:05Z"}],"graph_snapshots":[{"event_id":"sha256:26ceb7e0b33605f9a48d32a99230017448c4cbe2b788f741acff11e3f9118465","target":"graph","created_at":"2026-06-25T01:18:05Z","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/2606.25439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based models have achieved state-of-the-art performance in Time Series Forecasting (TSF), yet their evaluation remains dominated by pointwise error metrics such as Mean Squared Error (MSE), which quantify numerical accuracy but overlook structural properties of the forecast signal, including recurrent dynamics, oscillatory behavior, and phase alignment. As a result, forecasts exhibiting over-smoothing, phase shifts, or frequency distortions may achieve favorable error scores despite substantial structural degradation. To address this limitation, we propose TopoCast, a topology-dr","authors_text":"Sandareka Wickramanayake, Sandeepa Weerasekara","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T06:03:39Z","title":"TopoCast: A Topological Fidelity Framework for Evaluating Transformer-Based Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25439","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:de68d876268e35f0f378b0d0b6caacf77c105a76b7e49683efc5bfdf8fcbe816","target":"record","created_at":"2026-06-25T01:18:05Z","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":"c29e23a73a4502a91586685fe1277d99e480cc7016e9dac3b42ffa9c645c93f3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T06:03:39Z","title_canon_sha256":"daf36e069bbccfee16c8d6809ace125044e045fced68b4a335bfa87b0b2970f9"},"schema_version":"1.0","source":{"id":"2606.25439","kind":"arxiv","version":1}},"canonical_sha256":"6dfa3f068a4292bba749e7c72c30c95bb86761bd80af6f7544852eb981afa1f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6dfa3f068a4292bba749e7c72c30c95bb86761bd80af6f7544852eb981afa1f3","first_computed_at":"2026-06-25T01:18:05.368987Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:18:05.368987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OxaO1oRvuhxofcHNkQb+kWA7cVGKWN38OHN7H2XuQzxtEZM3c9Pqt0q7rplcOnvZXtL6l/yORTRvOTnsOJ2oBQ==","signature_status":"signed_v1","signed_at":"2026-06-25T01:18:05.369376Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25439","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de68d876268e35f0f378b0d0b6caacf77c105a76b7e49683efc5bfdf8fcbe816","sha256:26ceb7e0b33605f9a48d32a99230017448c4cbe2b788f741acff11e3f9118465"],"state_sha256":"51de04000cfc857a7518f9976def21d933b685b734291d4eac17ea017484b8f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xlNMQNC0/J3lmpVfMrAmpQvs4OuXAT0m4xCBBY8Qq6/FMZwTIp57kEnoSKW6PPgxWXYaZSa48lAUIF1uk0gADw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T04:06:19.542299Z","bundle_sha256":"14b7fe0cefde452619555dcef367aa1872675ff82058ca9f6f020f485a60b5f9"}}