{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:KSXVUNB7NJTNI7HI5JVLOH6XRC","short_pith_number":"pith:KSXVUNB7","canonical_record":{"source":{"id":"2507.20762","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-28T12:16:52Z","cross_cats_sorted":[],"title_canon_sha256":"fc72f6a23a26b836734d01aa072652ef965dbf7ab37bf6ea8d3efedbfc2a7d93","abstract_canon_sha256":"3bd61139951a1c7bf36b3184b44d30d3209c86aad74d971ba1108614c5b7eb08"},"schema_version":"1.0"},"canonical_sha256":"54af5a343f6a66d47ce8ea6ab71fd78887977d4370d204e102ef20d7c97e65ed","source":{"kind":"arxiv","id":"2507.20762","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.20762","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"arxiv_version","alias_value":"2507.20762v1","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.20762","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_12","alias_value":"KSXVUNB7NJTN","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_16","alias_value":"KSXVUNB7NJTNI7HI","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_8","alias_value":"KSXVUNB7","created_at":"2026-07-05T11:44:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:KSXVUNB7NJTNI7HI5JVLOH6XRC","target":"record","payload":{"canonical_record":{"source":{"id":"2507.20762","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-28T12:16:52Z","cross_cats_sorted":[],"title_canon_sha256":"fc72f6a23a26b836734d01aa072652ef965dbf7ab37bf6ea8d3efedbfc2a7d93","abstract_canon_sha256":"3bd61139951a1c7bf36b3184b44d30d3209c86aad74d971ba1108614c5b7eb08"},"schema_version":"1.0"},"canonical_sha256":"54af5a343f6a66d47ce8ea6ab71fd78887977d4370d204e102ef20d7c97e65ed","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:44:25.420504Z","signature_b64":"hAHxnEDq+EYyKeQ8djl8JbAlqUsE88TlpK3HnMZVzDDRNBNtc7qE7afV1oAjfiFMiEHm/BjAIFKFRHeyXCE2CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"54af5a343f6a66d47ce8ea6ab71fd78887977d4370d204e102ef20d7c97e65ed","last_reissued_at":"2026-07-05T11:44:25.420106Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:44:25.420106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.20762","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":"2026-07-05T11:44:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NIbPNZHoVUl/MWt3a5UdSsZOhUmeaGkzJF4CoMj7RsgPKZXPbV2O4gfk+gXsrh/4w9IenWWFTl2WlFTtZ5IsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:09:17.738700Z"},"content_sha256":"9003b43536a199f6c4c7fdafe62d711dfe6f4575d576dd065db81f6b16f68c4e","schema_version":"1.0","event_id":"sha256:9003b43536a199f6c4c7fdafe62d711dfe6f4575d576dd065db81f6b16f68c4e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:KSXVUNB7NJTNI7HI5JVLOH6XRC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Watermarking Large Language Model-based Time Series Forecasting","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Chaoqun Yang, Hongzhi Yin, Nguyen Quoc Viet Hung, Tong Chen, Wei Yuan, Yu Xing","submitted_at":"2025-07-28T12:16:52Z","abstract_excerpt":"Large Language Model-based Time Series Forecasting (LLMTS) has shown remarkable promise in handling complex and diverse temporal data, representing a significant step toward foundation models for time series analysis. However, this emerging paradigm introduces two critical challenges. First, the substantial commercial potential and resource-intensive development raise urgent concerns about intellectual property (IP) protection. Second, their powerful time series forecasting capabilities may be misused to produce misleading or fabricated deepfake time series data. To address these concerns, we "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.20762","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/2507.20762/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":"2026-07-05T11:44:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AAd05wXc1Bh6PAaSCjbg79aE/zTBFre+Tdi2M1bVRkCN1ew8JankcjC/HUN7n7yM4/u5KeYjN1GUOEGgjoDxDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:09:17.739281Z"},"content_sha256":"39250dfee711211b4cdf2ca268bdb88895f8152a8b1601dc62e2dc2dd88817b6","schema_version":"1.0","event_id":"sha256:39250dfee711211b4cdf2ca268bdb88895f8152a8b1601dc62e2dc2dd88817b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/bundle.json","state_url":"https://pith.science/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/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":"2026-08-23T05:09:17Z","links":{"resolver":"https://pith.science/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC","bundle":"https://pith.science/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/bundle.json","state":"https://pith.science/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KSXVUNB7NJTNI7HI5JVLOH6XRC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KSXVUNB7NJTNI7HI5JVLOH6XRC","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":"3bd61139951a1c7bf36b3184b44d30d3209c86aad74d971ba1108614c5b7eb08","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-28T12:16:52Z","title_canon_sha256":"fc72f6a23a26b836734d01aa072652ef965dbf7ab37bf6ea8d3efedbfc2a7d93"},"schema_version":"1.0","source":{"id":"2507.20762","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.20762","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"arxiv_version","alias_value":"2507.20762v1","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.20762","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_12","alias_value":"KSXVUNB7NJTN","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_16","alias_value":"KSXVUNB7NJTNI7HI","created_at":"2026-07-05T11:44:25Z"},{"alias_kind":"pith_short_8","alias_value":"KSXVUNB7","created_at":"2026-07-05T11:44:25Z"}],"graph_snapshots":[{"event_id":"sha256:39250dfee711211b4cdf2ca268bdb88895f8152a8b1601dc62e2dc2dd88817b6","target":"graph","created_at":"2026-07-05T11:44:25Z","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/2507.20762/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Model-based Time Series Forecasting (LLMTS) has shown remarkable promise in handling complex and diverse temporal data, representing a significant step toward foundation models for time series analysis. However, this emerging paradigm introduces two critical challenges. First, the substantial commercial potential and resource-intensive development raise urgent concerns about intellectual property (IP) protection. Second, their powerful time series forecasting capabilities may be misused to produce misleading or fabricated deepfake time series data. To address these concerns, we ","authors_text":"Chaoqun Yang, Hongzhi Yin, Nguyen Quoc Viet Hung, Tong Chen, Wei Yuan, Yu Xing","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-28T12:16:52Z","title":"Watermarking Large Language Model-based Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.20762","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":"sha256:9003b43536a199f6c4c7fdafe62d711dfe6f4575d576dd065db81f6b16f68c4e","target":"record","created_at":"2026-07-05T11:44:25Z","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":"3bd61139951a1c7bf36b3184b44d30d3209c86aad74d971ba1108614c5b7eb08","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-28T12:16:52Z","title_canon_sha256":"fc72f6a23a26b836734d01aa072652ef965dbf7ab37bf6ea8d3efedbfc2a7d93"},"schema_version":"1.0","source":{"id":"2507.20762","kind":"arxiv","version":1}},"canonical_sha256":"54af5a343f6a66d47ce8ea6ab71fd78887977d4370d204e102ef20d7c97e65ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"54af5a343f6a66d47ce8ea6ab71fd78887977d4370d204e102ef20d7c97e65ed","first_computed_at":"2026-07-05T11:44:25.420106Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:44:25.420106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hAHxnEDq+EYyKeQ8djl8JbAlqUsE88TlpK3HnMZVzDDRNBNtc7qE7afV1oAjfiFMiEHm/BjAIFKFRHeyXCE2CA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:44:25.420504Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.20762","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9003b43536a199f6c4c7fdafe62d711dfe6f4575d576dd065db81f6b16f68c4e","sha256:39250dfee711211b4cdf2ca268bdb88895f8152a8b1601dc62e2dc2dd88817b6"],"state_sha256":"22cae2edcb7ce0626cbe7f3a61bd23bfaedb276b8a2373c825fb89cb63212da8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"js1Jo6Tns1nJ2xmjGvuajou2Gn7VfOG6APddvE3QvtsSCu+LZidxLSzaWDIBlDcFsa3M0WxcTulPybMAODI8CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T05:09:17.745606Z","bundle_sha256":"4c101f60e0298833bbbdfb6bd9cffb167bdc789a7544c0074950002c8ba63e61"}}