{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:R2M44POHKLPHKMDKHIC2VZTTDK","short_pith_number":"pith:R2M44POH","canonical_record":{"source":{"id":"2504.14519","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-20T07:33:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"347eac57c79cf74bcc1dae54aa59cec48834c3157cf40a7511856cb2c0c5d735","abstract_canon_sha256":"6a9649aa561d520f9b7d67614165d4fd274ef3594702beff0b02c5659c67211c"},"schema_version":"1.0"},"canonical_sha256":"8e99ce3dc752de75306a3a05aae6731a9b35b189f789e3894312dc7a84cd7ae3","source":{"kind":"arxiv","id":"2504.14519","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.14519","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"arxiv_version","alias_value":"2504.14519v1","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.14519","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_12","alias_value":"R2M44POHKLPH","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_16","alias_value":"R2M44POHKLPHKMDK","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_8","alias_value":"R2M44POH","created_at":"2026-07-05T10:51:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:R2M44POHKLPHKMDKHIC2VZTTDK","target":"record","payload":{"canonical_record":{"source":{"id":"2504.14519","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-20T07:33:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"347eac57c79cf74bcc1dae54aa59cec48834c3157cf40a7511856cb2c0c5d735","abstract_canon_sha256":"6a9649aa561d520f9b7d67614165d4fd274ef3594702beff0b02c5659c67211c"},"schema_version":"1.0"},"canonical_sha256":"8e99ce3dc752de75306a3a05aae6731a9b35b189f789e3894312dc7a84cd7ae3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:51:44.679652Z","signature_b64":"CDmtiNGDBEUDddMiQvRUZL0xx+aB3HrP6/Hcd+dJuMJUj4avPsT7QSxLKoHqhkcgKOjQjx17AD5xYSF8shxcCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e99ce3dc752de75306a3a05aae6731a9b35b189f789e3894312dc7a84cd7ae3","last_reissued_at":"2026-07-05T10:51:44.679126Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:51:44.679126Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.14519","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":"2026-07-05T10:51:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/cz3WLdBO3qHOsBjavt7Z3rt659jB2JxQ2SnOtu31GduKfJ9/xWgWfH2lU/NPwZR5NA69CoqpyKumcXNrKl3Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:14:07.042654Z"},"content_sha256":"6a71435ffd253081c98b1aa0ce95cd87d5c2324b268963978554b74ca3dbae38","schema_version":"1.0","event_id":"sha256:6a71435ffd253081c98b1aa0ce95cd87d5c2324b268963978554b74ca3dbae38"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:R2M44POHKLPHKMDKHIC2VZTTDK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SlimPipe: Memory-Thrifty and Efficient Pipeline Parallelism for Long-Context LLM Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Bin Chen, Chengru Song, Di Zhang, Tailing Yuan, Wei Zhang, Yuliang Liu, Zhouyang Li","submitted_at":"2025-04-20T07:33:33Z","abstract_excerpt":"Pipeline Parallelism (PP) serves as a crucial technique for training Large Language Models (LLMs), owing to its capability to alleviate memory pressure from model states with relatively low communication overhead. However, in long-context scenarios, existing pipeline parallelism methods fail to address the substantial activation memory pressure, primarily due to the peak memory consumption resulting from the accumulation of activations across multiple microbatches. Moreover, these approaches inevitably introduce considerable pipeline bubbles, further hindering efficiency.\n  To tackle these cha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.14519","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/2504.14519/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":"2026-07-05T10:51:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qnaxMOxqM9eCFazEu3jj2PqtPXpVeqwcOZZkaH6kb6grFGFX35XiEqsB/vZlaRprm6j82aCr8j3GLhRojaBwCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:14:07.043564Z"},"content_sha256":"6ffd7de78e9bd906d908ba1dd2f5166e99712ca782405464fc0f41c90d182ba1","schema_version":"1.0","event_id":"sha256:6ffd7de78e9bd906d908ba1dd2f5166e99712ca782405464fc0f41c90d182ba1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R2M44POHKLPHKMDKHIC2VZTTDK/bundle.json","state_url":"https://pith.science/pith/R2M44POHKLPHKMDKHIC2VZTTDK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R2M44POHKLPHKMDKHIC2VZTTDK/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":"2026-08-05T04:14:07Z","links":{"resolver":"https://pith.science/pith/R2M44POHKLPHKMDKHIC2VZTTDK","bundle":"https://pith.science/pith/R2M44POHKLPHKMDKHIC2VZTTDK/bundle.json","state":"https://pith.science/pith/R2M44POHKLPHKMDKHIC2VZTTDK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R2M44POHKLPHKMDKHIC2VZTTDK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:R2M44POHKLPHKMDKHIC2VZTTDK","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":"6a9649aa561d520f9b7d67614165d4fd274ef3594702beff0b02c5659c67211c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-20T07:33:33Z","title_canon_sha256":"347eac57c79cf74bcc1dae54aa59cec48834c3157cf40a7511856cb2c0c5d735"},"schema_version":"1.0","source":{"id":"2504.14519","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.14519","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"arxiv_version","alias_value":"2504.14519v1","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.14519","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_12","alias_value":"R2M44POHKLPH","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_16","alias_value":"R2M44POHKLPHKMDK","created_at":"2026-07-05T10:51:44Z"},{"alias_kind":"pith_short_8","alias_value":"R2M44POH","created_at":"2026-07-05T10:51:44Z"}],"graph_snapshots":[{"event_id":"sha256:6ffd7de78e9bd906d908ba1dd2f5166e99712ca782405464fc0f41c90d182ba1","target":"graph","created_at":"2026-07-05T10:51:44Z","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/2504.14519/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Pipeline Parallelism (PP) serves as a crucial technique for training Large Language Models (LLMs), owing to its capability to alleviate memory pressure from model states with relatively low communication overhead. However, in long-context scenarios, existing pipeline parallelism methods fail to address the substantial activation memory pressure, primarily due to the peak memory consumption resulting from the accumulation of activations across multiple microbatches. Moreover, these approaches inevitably introduce considerable pipeline bubbles, further hindering efficiency.\n  To tackle these cha","authors_text":"Bin Chen, Chengru Song, Di Zhang, Tailing Yuan, Wei Zhang, Yuliang Liu, Zhouyang Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-20T07:33:33Z","title":"SlimPipe: Memory-Thrifty and Efficient Pipeline Parallelism for Long-Context LLM Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.14519","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":"sha256:6a71435ffd253081c98b1aa0ce95cd87d5c2324b268963978554b74ca3dbae38","target":"record","created_at":"2026-07-05T10:51:44Z","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":"6a9649aa561d520f9b7d67614165d4fd274ef3594702beff0b02c5659c67211c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-20T07:33:33Z","title_canon_sha256":"347eac57c79cf74bcc1dae54aa59cec48834c3157cf40a7511856cb2c0c5d735"},"schema_version":"1.0","source":{"id":"2504.14519","kind":"arxiv","version":1}},"canonical_sha256":"8e99ce3dc752de75306a3a05aae6731a9b35b189f789e3894312dc7a84cd7ae3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e99ce3dc752de75306a3a05aae6731a9b35b189f789e3894312dc7a84cd7ae3","first_computed_at":"2026-07-05T10:51:44.679126Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:51:44.679126Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CDmtiNGDBEUDddMiQvRUZL0xx+aB3HrP6/Hcd+dJuMJUj4avPsT7QSxLKoHqhkcgKOjQjx17AD5xYSF8shxcCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:51:44.679652Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.14519","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a71435ffd253081c98b1aa0ce95cd87d5c2324b268963978554b74ca3dbae38","sha256:6ffd7de78e9bd906d908ba1dd2f5166e99712ca782405464fc0f41c90d182ba1"],"state_sha256":"1e2e2ac664f932e8ca4c2ed9895f235a546bb7522714f66e9667f6d7ad64c791"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"opPTAw4VdRDTbwk7E/gMvZwgLH9MJlT7begFzBuodmc9f8kSWYVrXxIGO6uuKGK9S+12qUpVTDdYmF+7VKbSAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T04:14:07.049119Z","bundle_sha256":"7d986085832efdd6bb43cb1db73039541cfcbde26d8da368b35375f5be1c4b03"}}