{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MIVZPVIPGPVXALAGHPEIQPZXMO","short_pith_number":"pith:MIVZPVIP","canonical_record":{"source":{"id":"2501.08455","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-14T22:00:01Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"1a10331040559837cf7cfba855c9135386bd475d933c2a0bd7ba84dc1a4a5d1a","abstract_canon_sha256":"d5e98a6be73f2261d056646816e916753683124776d209fd6edfeb8dda580937"},"schema_version":"1.0"},"canonical_sha256":"622b97d50f33eb702c063bc8883f3763bdd18efc111ae18c82c99190323d686e","source":{"kind":"arxiv","id":"2501.08455","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.08455","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"arxiv_version","alias_value":"2501.08455v1","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.08455","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_12","alias_value":"MIVZPVIPGPVX","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_16","alias_value":"MIVZPVIPGPVXALAG","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_8","alias_value":"MIVZPVIP","created_at":"2026-07-05T10:01:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MIVZPVIPGPVXALAGHPEIQPZXMO","target":"record","payload":{"canonical_record":{"source":{"id":"2501.08455","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-14T22:00:01Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"1a10331040559837cf7cfba855c9135386bd475d933c2a0bd7ba84dc1a4a5d1a","abstract_canon_sha256":"d5e98a6be73f2261d056646816e916753683124776d209fd6edfeb8dda580937"},"schema_version":"1.0"},"canonical_sha256":"622b97d50f33eb702c063bc8883f3763bdd18efc111ae18c82c99190323d686e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:01:20.205060Z","signature_b64":"KEFnMaHn3qvdoHw7uWDvr773JbMBB565hd1A19vSjZOcSw9xhVzpHI9jW12WyrdsUCq34t2Y8D0JMyGko1gvCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"622b97d50f33eb702c063bc8883f3763bdd18efc111ae18c82c99190323d686e","last_reissued_at":"2026-07-05T10:01:20.204658Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:01:20.204658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.08455","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":"2026-07-05T10:01:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EuZHLqTK3A8k2MMyeUQtrIaJrFiHAaSFMBNkU0h5J1imqM7SAe35LRj5k6Ap+moPZRzSU2X57HWOHgur2H3xCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:19:28.434001Z"},"content_sha256":"2428e749cc08c1591c44efa920fe806bbcf55fbe20e1dac28b3910f319b50e58","schema_version":"1.0","event_id":"sha256:2428e749cc08c1591c44efa920fe806bbcf55fbe20e1dac28b3910f319b50e58"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MIVZPVIPGPVXALAGHPEIQPZXMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Keras Sig: Efficient Path Signature Computation on GPU in Keras 3","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.LG","authors_text":"Hugo Inzirillo, R\\'emi Genet","submitted_at":"2025-01-14T22:00:01Z","abstract_excerpt":"In this paper we introduce Keras Sig a high-performance pythonic library designed to compute path signature for deep learning applications. Entirely built in Keras 3, \\textit{Keras Sig} leverages the seamless integration with the mostly used deep learning backends such as PyTorch, JAX and TensorFlow. Inspired by Kidger and Lyons (2021),we proposed a novel approach reshaping signature calculations to leverage GPU parallelism. This adjustment allows us to reduce the training time by 55\\% and 5 to 10-fold improvements in direct signature computation compared to existing methods, while maintaining"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.08455","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/2501.08455/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":"2026-07-05T10:01:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dBT5ZMpQ2LFfMuhv/zyN7kIjJUK/UlaJtUEQ0oSUYkrnoYpiugjoP7/sTYLnQcoFeOIUCioWCispT4cP7Wt4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:19:28.434527Z"},"content_sha256":"911bf2a616e4bb518e5551c1dad5ef9742390ff91ea2f661f2d770cd2cf0a982","schema_version":"1.0","event_id":"sha256:911bf2a616e4bb518e5551c1dad5ef9742390ff91ea2f661f2d770cd2cf0a982"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/bundle.json","state_url":"https://pith.science/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/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":"2026-08-09T06:19:28Z","links":{"resolver":"https://pith.science/pith/MIVZPVIPGPVXALAGHPEIQPZXMO","bundle":"https://pith.science/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/bundle.json","state":"https://pith.science/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MIVZPVIPGPVXALAGHPEIQPZXMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MIVZPVIPGPVXALAGHPEIQPZXMO","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":"d5e98a6be73f2261d056646816e916753683124776d209fd6edfeb8dda580937","cross_cats_sorted":["cs.DC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-14T22:00:01Z","title_canon_sha256":"1a10331040559837cf7cfba855c9135386bd475d933c2a0bd7ba84dc1a4a5d1a"},"schema_version":"1.0","source":{"id":"2501.08455","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.08455","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"arxiv_version","alias_value":"2501.08455v1","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.08455","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_12","alias_value":"MIVZPVIPGPVX","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_16","alias_value":"MIVZPVIPGPVXALAG","created_at":"2026-07-05T10:01:20Z"},{"alias_kind":"pith_short_8","alias_value":"MIVZPVIP","created_at":"2026-07-05T10:01:20Z"}],"graph_snapshots":[{"event_id":"sha256:911bf2a616e4bb518e5551c1dad5ef9742390ff91ea2f661f2d770cd2cf0a982","target":"graph","created_at":"2026-07-05T10:01:20Z","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/2501.08455/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we introduce Keras Sig a high-performance pythonic library designed to compute path signature for deep learning applications. Entirely built in Keras 3, \\textit{Keras Sig} leverages the seamless integration with the mostly used deep learning backends such as PyTorch, JAX and TensorFlow. Inspired by Kidger and Lyons (2021),we proposed a novel approach reshaping signature calculations to leverage GPU parallelism. This adjustment allows us to reduce the training time by 55\\% and 5 to 10-fold improvements in direct signature computation compared to existing methods, while maintaining","authors_text":"Hugo Inzirillo, R\\'emi Genet","cross_cats":["cs.DC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-14T22:00:01Z","title":"Keras Sig: Efficient Path Signature Computation on GPU in Keras 3"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.08455","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":"sha256:2428e749cc08c1591c44efa920fe806bbcf55fbe20e1dac28b3910f319b50e58","target":"record","created_at":"2026-07-05T10:01:20Z","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":"d5e98a6be73f2261d056646816e916753683124776d209fd6edfeb8dda580937","cross_cats_sorted":["cs.DC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-14T22:00:01Z","title_canon_sha256":"1a10331040559837cf7cfba855c9135386bd475d933c2a0bd7ba84dc1a4a5d1a"},"schema_version":"1.0","source":{"id":"2501.08455","kind":"arxiv","version":1}},"canonical_sha256":"622b97d50f33eb702c063bc8883f3763bdd18efc111ae18c82c99190323d686e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"622b97d50f33eb702c063bc8883f3763bdd18efc111ae18c82c99190323d686e","first_computed_at":"2026-07-05T10:01:20.204658Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:01:20.204658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KEFnMaHn3qvdoHw7uWDvr773JbMBB565hd1A19vSjZOcSw9xhVzpHI9jW12WyrdsUCq34t2Y8D0JMyGko1gvCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:01:20.205060Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.08455","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2428e749cc08c1591c44efa920fe806bbcf55fbe20e1dac28b3910f319b50e58","sha256:911bf2a616e4bb518e5551c1dad5ef9742390ff91ea2f661f2d770cd2cf0a982"],"state_sha256":"4bade2700f6c82695cd5e47e54cfd28615af19301d4886537a782ec1de9da602"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gYHVQDqKvpoNVT2c4cH95YRigeS3CEM9V9/PSPWulTQpDd6RdxZFJd6r4HT2qc8UGN5sp/WktWAXjn3m6opgCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T06:19:28.437986Z","bundle_sha256":"6703a6d5f5d6704a5a54fa826d84b84cd88f56f87a817f44a56ba5ac53a76962"}}