{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:C3QEFDNTUZJLMVKEQVMNWQYEAP","short_pith_number":"pith:C3QEFDNT","canonical_record":{"source":{"id":"2406.06962","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T05:44:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9b720096be535745ecfaaf3255433ea21aa8b53a41c8a7f5dd617a4435fccb13","abstract_canon_sha256":"e0f240611fbedca2a69febd2cc0ec1ca8fe778527f74b79ef9151d8961d91417"},"schema_version":"1.0"},"canonical_sha256":"16e0428db3a652b655448558db430403f7301c005b8b46cb4d76b66c3fd04e8a","source":{"kind":"arxiv","id":"2406.06962","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.06962","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"2406.06962v1","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06962","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"C3QEFDNTUZJL","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_16","alias_value":"C3QEFDNTUZJLMVKE","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_8","alias_value":"C3QEFDNT","created_at":"2026-07-05T08:30:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:C3QEFDNTUZJLMVKEQVMNWQYEAP","target":"record","payload":{"canonical_record":{"source":{"id":"2406.06962","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T05:44:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9b720096be535745ecfaaf3255433ea21aa8b53a41c8a7f5dd617a4435fccb13","abstract_canon_sha256":"e0f240611fbedca2a69febd2cc0ec1ca8fe778527f74b79ef9151d8961d91417"},"schema_version":"1.0"},"canonical_sha256":"16e0428db3a652b655448558db430403f7301c005b8b46cb4d76b66c3fd04e8a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:30:16.071902Z","signature_b64":"hfjZaUawRZIFv8CoGQF/i+gniiATCGjmfgFNa2qiTUhKEgbThmXSlCl7uYUs0IgRLzX1SXRnqVDLPQ088ZYsAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16e0428db3a652b655448558db430403f7301c005b8b46cb4d76b66c3fd04e8a","last_reissued_at":"2026-07-05T08:30:16.071483Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:30:16.071483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.06962","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":"2026-07-05T08:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XvRJz219oSjAr/TJwf4HvfOMiXDiHB1wmNs5u6qkBVEDmMDR5Qg0k6syBE+oshbqjmjkYGAyCpnLcpd/C0INDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T20:23:08.629645Z"},"content_sha256":"51bfeac6bd90f86c192140523916c6bc624a5a4fd4a17b8936a9d7cc1b451f3d","schema_version":"1.0","event_id":"sha256:51bfeac6bd90f86c192140523916c6bc624a5a4fd4a17b8936a9d7cc1b451f3d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:C3QEFDNTUZJLMVKEQVMNWQYEAP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evolving Subnetwork Training for Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Da Ma, Hanqi Li, Kai Yu, Lu Chen, Su Zhu, Zijian Wu","submitted_at":"2024-06-11T05:44:56Z","abstract_excerpt":"Large language models have ushered in a new era of artificial intelligence research. However, their substantial training costs hinder further development and widespread adoption. In this paper, inspired by the redundancy in the parameters of large language models, we propose a novel training paradigm: Evolving Subnetwork Training (EST). EST samples subnetworks from the layers of the large language model and from commonly used modules within each layer, Multi-Head Attention (MHA) and Multi-Layer Perceptron (MLP). By gradually increasing the size of the subnetworks during the training process, E"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06962","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/2406.06962/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":"2026-07-05T08:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6+A9usGDZL0vZJODSu8wXC6OjJueCKHI7xRxEBlzArDiXk1l7L0Eh1USqXRLoKHd6RvemQsZvpqqDgli8nU8DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T20:23:08.630255Z"},"content_sha256":"42f1c9750a5ed9e5ad623ce9d9cce56d72c083a2c9ca323ae27c45b05db7bb82","schema_version":"1.0","event_id":"sha256:42f1c9750a5ed9e5ad623ce9d9cce56d72c083a2c9ca323ae27c45b05db7bb82"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/bundle.json","state_url":"https://pith.science/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/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":"2026-08-09T20:23:08Z","links":{"resolver":"https://pith.science/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP","bundle":"https://pith.science/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/bundle.json","state":"https://pith.science/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C3QEFDNTUZJLMVKEQVMNWQYEAP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:C3QEFDNTUZJLMVKEQVMNWQYEAP","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":"e0f240611fbedca2a69febd2cc0ec1ca8fe778527f74b79ef9151d8961d91417","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T05:44:56Z","title_canon_sha256":"9b720096be535745ecfaaf3255433ea21aa8b53a41c8a7f5dd617a4435fccb13"},"schema_version":"1.0","source":{"id":"2406.06962","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.06962","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"2406.06962v1","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06962","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"C3QEFDNTUZJL","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_16","alias_value":"C3QEFDNTUZJLMVKE","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_8","alias_value":"C3QEFDNT","created_at":"2026-07-05T08:30:16Z"}],"graph_snapshots":[{"event_id":"sha256:42f1c9750a5ed9e5ad623ce9d9cce56d72c083a2c9ca323ae27c45b05db7bb82","target":"graph","created_at":"2026-07-05T08:30:16Z","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/2406.06962/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models have ushered in a new era of artificial intelligence research. However, their substantial training costs hinder further development and widespread adoption. In this paper, inspired by the redundancy in the parameters of large language models, we propose a novel training paradigm: Evolving Subnetwork Training (EST). EST samples subnetworks from the layers of the large language model and from commonly used modules within each layer, Multi-Head Attention (MHA) and Multi-Layer Perceptron (MLP). By gradually increasing the size of the subnetworks during the training process, E","authors_text":"Da Ma, Hanqi Li, Kai Yu, Lu Chen, Su Zhu, Zijian Wu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T05:44:56Z","title":"Evolving Subnetwork Training for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06962","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":"sha256:51bfeac6bd90f86c192140523916c6bc624a5a4fd4a17b8936a9d7cc1b451f3d","target":"record","created_at":"2026-07-05T08:30:16Z","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":"e0f240611fbedca2a69febd2cc0ec1ca8fe778527f74b79ef9151d8961d91417","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T05:44:56Z","title_canon_sha256":"9b720096be535745ecfaaf3255433ea21aa8b53a41c8a7f5dd617a4435fccb13"},"schema_version":"1.0","source":{"id":"2406.06962","kind":"arxiv","version":1}},"canonical_sha256":"16e0428db3a652b655448558db430403f7301c005b8b46cb4d76b66c3fd04e8a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16e0428db3a652b655448558db430403f7301c005b8b46cb4d76b66c3fd04e8a","first_computed_at":"2026-07-05T08:30:16.071483Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:30:16.071483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hfjZaUawRZIFv8CoGQF/i+gniiATCGjmfgFNa2qiTUhKEgbThmXSlCl7uYUs0IgRLzX1SXRnqVDLPQ088ZYsAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:30:16.071902Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.06962","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:51bfeac6bd90f86c192140523916c6bc624a5a4fd4a17b8936a9d7cc1b451f3d","sha256:42f1c9750a5ed9e5ad623ce9d9cce56d72c083a2c9ca323ae27c45b05db7bb82"],"state_sha256":"05161cb3139132c76b7574617cb28094206c90e9853296613abe08019d793439"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hxEv4jvBWIi8rPQn8qtAGv2jkWFjL3qfFEvZZziPnxRgyiGODZ4Rl/1eClu5xPZrVq4nrU7L39j7oP6X22pcDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T20:23:08.634778Z","bundle_sha256":"e12f837cd7a0297b2b33cbc1f31bfa2bda7524b29e5c7526a5de8248a3f43cca"}}