{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:R6OUSJA3G3TTCVTD4EJMQQWMLL","short_pith_number":"pith:R6OUSJA3","canonical_record":{"source":{"id":"2408.03865","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T16:13:43Z","cross_cats_sorted":[],"title_canon_sha256":"d83b2f5f0843ee89d40fece8396ed556504e266e3c49d370a5c6abd1f68961dc","abstract_canon_sha256":"1fd904cc887d9af5d39d60954ce379bef9c6c585aeb36412fb63d2d273480b3e"},"schema_version":"1.0"},"canonical_sha256":"8f9d49241b36e7315663e112c842cc5adad2b3103f85a802b6a3999745e0fe30","source":{"kind":"arxiv","id":"2408.03865","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03865","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03865v2","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03865","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_12","alias_value":"R6OUSJA3G3TT","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_16","alias_value":"R6OUSJA3G3TTCVTD","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_8","alias_value":"R6OUSJA3","created_at":"2026-07-05T08:57:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:R6OUSJA3G3TTCVTD4EJMQQWMLL","target":"record","payload":{"canonical_record":{"source":{"id":"2408.03865","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T16:13:43Z","cross_cats_sorted":[],"title_canon_sha256":"d83b2f5f0843ee89d40fece8396ed556504e266e3c49d370a5c6abd1f68961dc","abstract_canon_sha256":"1fd904cc887d9af5d39d60954ce379bef9c6c585aeb36412fb63d2d273480b3e"},"schema_version":"1.0"},"canonical_sha256":"8f9d49241b36e7315663e112c842cc5adad2b3103f85a802b6a3999745e0fe30","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:57:40.182754Z","signature_b64":"CCRotkJKqXe7dBE2/evAkh+I0W2pFqhyBW/Wd8vJSemIxxY91mT08GWt7QKY07QpSIrpI3po5gSjjSD5pLoAAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8f9d49241b36e7315663e112c842cc5adad2b3103f85a802b6a3999745e0fe30","last_reissued_at":"2026-07-05T08:57:40.182245Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:57:40.182245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.03865","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:57:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YXBLq9fj97604ozOJ5HWP+hINFqfuURp+Pz+BO6qkC7unmfn6EqBDytoLbw7g2rO1wkoBHF58h53QMKo2NI2DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:08:34.559021Z"},"content_sha256":"6af0068890477ff99dabfc04923b672fca7e3e5181e4251aa0f5fc3fd1ce8ab8","schema_version":"1.0","event_id":"sha256:6af0068890477ff99dabfc04923b672fca7e3e5181e4251aa0f5fc3fd1ce8ab8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:R6OUSJA3G3TTCVTD4EJMQQWMLL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PackMamba: Efficient Processing of Variable-Length Sequences in Mamba training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Haoran Xu, Rong Fu, Xingcheng Zhang, Zerui Wang, Zheng Cai, Zhilin Pei, Zhongling Su, Ziqian Liu","submitted_at":"2024-08-07T16:13:43Z","abstract_excerpt":"With the evolution of large language models, traditional Transformer models become computationally demanding for lengthy sequences due to the quadratic growth in computation with respect to the sequence length. Mamba, emerging as a groundbreaking architecture in the field of generative AI, demonstrates remarkable proficiency in handling elongated sequences with reduced computational and memory complexity. Nevertheless, the existing training framework of Mamba presents inefficiency with variable-length sequence inputs. Either single-sequence training results in low GPU utilization, or batched p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03865","kind":"arxiv","version":2},"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/2408.03865/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":"2026-07-05T08:57:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u4bjQUiSwHXzyo+pBvSid/SVtMDtO2td2sJvXFoyixqS6x5aDYWEcyL7n74toCGEu68BYJKMZdDNQNWQ2E8aDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:08:34.559874Z"},"content_sha256":"62059b5790c92c50d928b1cf9530cb47e16e8c1abaa12803c05ee9a344bc21e0","schema_version":"1.0","event_id":"sha256:62059b5790c92c50d928b1cf9530cb47e16e8c1abaa12803c05ee9a344bc21e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/bundle.json","state_url":"https://pith.science/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/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":"2026-08-06T02:08:34Z","links":{"resolver":"https://pith.science/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL","bundle":"https://pith.science/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/bundle.json","state":"https://pith.science/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R6OUSJA3G3TTCVTD4EJMQQWMLL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:R6OUSJA3G3TTCVTD4EJMQQWMLL","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":"1fd904cc887d9af5d39d60954ce379bef9c6c585aeb36412fb63d2d273480b3e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T16:13:43Z","title_canon_sha256":"d83b2f5f0843ee89d40fece8396ed556504e266e3c49d370a5c6abd1f68961dc"},"schema_version":"1.0","source":{"id":"2408.03865","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03865","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03865v2","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03865","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_12","alias_value":"R6OUSJA3G3TT","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_16","alias_value":"R6OUSJA3G3TTCVTD","created_at":"2026-07-05T08:57:40Z"},{"alias_kind":"pith_short_8","alias_value":"R6OUSJA3","created_at":"2026-07-05T08:57:40Z"}],"graph_snapshots":[{"event_id":"sha256:62059b5790c92c50d928b1cf9530cb47e16e8c1abaa12803c05ee9a344bc21e0","target":"graph","created_at":"2026-07-05T08:57:40Z","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/2408.03865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the evolution of large language models, traditional Transformer models become computationally demanding for lengthy sequences due to the quadratic growth in computation with respect to the sequence length. Mamba, emerging as a groundbreaking architecture in the field of generative AI, demonstrates remarkable proficiency in handling elongated sequences with reduced computational and memory complexity. Nevertheless, the existing training framework of Mamba presents inefficiency with variable-length sequence inputs. Either single-sequence training results in low GPU utilization, or batched p","authors_text":"Haoran Xu, Rong Fu, Xingcheng Zhang, Zerui Wang, Zheng Cai, Zhilin Pei, Zhongling Su, Ziqian Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T16:13:43Z","title":"PackMamba: Efficient Processing of Variable-Length Sequences in Mamba training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03865","kind":"arxiv","version":2},"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":"sha256:6af0068890477ff99dabfc04923b672fca7e3e5181e4251aa0f5fc3fd1ce8ab8","target":"record","created_at":"2026-07-05T08:57:40Z","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":"1fd904cc887d9af5d39d60954ce379bef9c6c585aeb36412fb63d2d273480b3e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T16:13:43Z","title_canon_sha256":"d83b2f5f0843ee89d40fece8396ed556504e266e3c49d370a5c6abd1f68961dc"},"schema_version":"1.0","source":{"id":"2408.03865","kind":"arxiv","version":2}},"canonical_sha256":"8f9d49241b36e7315663e112c842cc5adad2b3103f85a802b6a3999745e0fe30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f9d49241b36e7315663e112c842cc5adad2b3103f85a802b6a3999745e0fe30","first_computed_at":"2026-07-05T08:57:40.182245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:57:40.182245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CCRotkJKqXe7dBE2/evAkh+I0W2pFqhyBW/Wd8vJSemIxxY91mT08GWt7QKY07QpSIrpI3po5gSjjSD5pLoAAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:57:40.182754Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.03865","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6af0068890477ff99dabfc04923b672fca7e3e5181e4251aa0f5fc3fd1ce8ab8","sha256:62059b5790c92c50d928b1cf9530cb47e16e8c1abaa12803c05ee9a344bc21e0"],"state_sha256":"e39873d03d255fdb6d186aba1ac9a44438b581a12e03b4d50d33feacefdf3741"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mTghaYDNeUa8HYY84KtdykKJb/7X28I9SwfOXZ9VmSeaA+WAsVK6bYopf8/M7nC+8gLfGGCcYUi6EhbHbL2QDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T02:08:34.566886Z","bundle_sha256":"7c4746b2ef46c1e33fa280f954712051b3b339a65335fdad98e6805f9601d18e"}}