{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4W2J2ZDQMU36TX365WEKGNBD3Q","short_pith_number":"pith:4W2J2ZDQ","canonical_record":{"source":{"id":"2402.17946","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-28T00:09:07Z","cross_cats_sorted":[],"title_canon_sha256":"3e69ca3d2aa7cfad6e37340054a5b6e7cdc5cf8912995a7aa5353dbb107ef28c","abstract_canon_sha256":"4a3e9c1ca75cd3a56c00b1dfaf332a899b394e0f321193c3e91ddfd3cb4afffe"},"schema_version":"1.0"},"canonical_sha256":"e5b49d64706537e9df7eed88a33423dc278c1430d75ba807f33d9c8de00dbd25","source":{"kind":"arxiv","id":"2402.17946","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17946","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17946v4","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17946","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_12","alias_value":"4W2J2ZDQMU36","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_16","alias_value":"4W2J2ZDQMU36TX36","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_8","alias_value":"4W2J2ZDQ","created_at":"2026-07-05T09:29:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4W2J2ZDQMU36TX365WEKGNBD3Q","target":"record","payload":{"canonical_record":{"source":{"id":"2402.17946","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-28T00:09:07Z","cross_cats_sorted":[],"title_canon_sha256":"3e69ca3d2aa7cfad6e37340054a5b6e7cdc5cf8912995a7aa5353dbb107ef28c","abstract_canon_sha256":"4a3e9c1ca75cd3a56c00b1dfaf332a899b394e0f321193c3e91ddfd3cb4afffe"},"schema_version":"1.0"},"canonical_sha256":"e5b49d64706537e9df7eed88a33423dc278c1430d75ba807f33d9c8de00dbd25","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:29:26.515400Z","signature_b64":"YfxX4/TQ4/9UOZHMvJuK1ZJvr5x9F7nKY1bgXVVlN4aLoy9BjN+5SGobDXkr3+Bk6DQfCQKdUi1dL4kXQ6Z5Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5b49d64706537e9df7eed88a33423dc278c1430d75ba807f33d9c8de00dbd25","last_reissued_at":"2026-07-05T09:29:26.514904Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:29:26.514904Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.17946","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:29:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3eK7ZVVLuN97zsU9FSBIlfM8LxzwqCfM/jsNPLnPNBS4orLUbqsyo/2j5rDJFn6t/iG1CVA+ptjeiwziQXmyDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T13:56:23.256587Z"},"content_sha256":"98657b61b491e34fdbe64336870505862d19baf23f4b7d2b44a6c24aa915fafc","schema_version":"1.0","event_id":"sha256:98657b61b491e34fdbe64336870505862d19baf23f4b7d2b44a6c24aa915fafc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4W2J2ZDQMU36TX365WEKGNBD3Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SparseLLM: Towards Global Pruning for Pre-trained Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chen Ling, Guangji Bai, Kibaek Kim, Liang Zhao, Yijiang Li","submitted_at":"2024-02-28T00:09:07Z","abstract_excerpt":"The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands. Pruning has emerged as a pivotal compression strategy, introducing sparsity to enhance both memory and computational efficiency. Yet, traditional global pruning is impractical for LLMs due to scalability issues, while local pruning, despite its efficiency, leads to suboptimal solutions. Addressing these challenges, we propose SparseLLM, a novel framework that redefines the global pruning process into manageable, coordinated subprob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17946","kind":"arxiv","version":4},"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/2402.17946/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":"2026-07-05T09:29:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9gH6wIvzmZ19euMUv0K3a1DdsBM+f/7FPvseUj7uT1aHbZNFwj0BIK4A5GnbXEhdJqTeCN6DLWFMEAwMVeZaBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T13:56:23.257165Z"},"content_sha256":"b7a659c27adbd44f03d660194bf7a4fc32f5f175d576ff4f2d8f67bee32049f7","schema_version":"1.0","event_id":"sha256:b7a659c27adbd44f03d660194bf7a4fc32f5f175d576ff4f2d8f67bee32049f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/bundle.json","state_url":"https://pith.science/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/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":"2026-08-15T13:56:23Z","links":{"resolver":"https://pith.science/pith/4W2J2ZDQMU36TX365WEKGNBD3Q","bundle":"https://pith.science/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/bundle.json","state":"https://pith.science/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4W2J2ZDQMU36TX365WEKGNBD3Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4W2J2ZDQMU36TX365WEKGNBD3Q","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":"4a3e9c1ca75cd3a56c00b1dfaf332a899b394e0f321193c3e91ddfd3cb4afffe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-28T00:09:07Z","title_canon_sha256":"3e69ca3d2aa7cfad6e37340054a5b6e7cdc5cf8912995a7aa5353dbb107ef28c"},"schema_version":"1.0","source":{"id":"2402.17946","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17946","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17946v4","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17946","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_12","alias_value":"4W2J2ZDQMU36","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_16","alias_value":"4W2J2ZDQMU36TX36","created_at":"2026-07-05T09:29:26Z"},{"alias_kind":"pith_short_8","alias_value":"4W2J2ZDQ","created_at":"2026-07-05T09:29:26Z"}],"graph_snapshots":[{"event_id":"sha256:b7a659c27adbd44f03d660194bf7a4fc32f5f175d576ff4f2d8f67bee32049f7","target":"graph","created_at":"2026-07-05T09:29:26Z","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/2402.17946/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands. Pruning has emerged as a pivotal compression strategy, introducing sparsity to enhance both memory and computational efficiency. Yet, traditional global pruning is impractical for LLMs due to scalability issues, while local pruning, despite its efficiency, leads to suboptimal solutions. Addressing these challenges, we propose SparseLLM, a novel framework that redefines the global pruning process into manageable, coordinated subprob","authors_text":"Chen Ling, Guangji Bai, Kibaek Kim, Liang Zhao, Yijiang Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-28T00:09:07Z","title":"SparseLLM: Towards Global Pruning for Pre-trained Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17946","kind":"arxiv","version":4},"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":"sha256:98657b61b491e34fdbe64336870505862d19baf23f4b7d2b44a6c24aa915fafc","target":"record","created_at":"2026-07-05T09:29:26Z","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":"4a3e9c1ca75cd3a56c00b1dfaf332a899b394e0f321193c3e91ddfd3cb4afffe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-28T00:09:07Z","title_canon_sha256":"3e69ca3d2aa7cfad6e37340054a5b6e7cdc5cf8912995a7aa5353dbb107ef28c"},"schema_version":"1.0","source":{"id":"2402.17946","kind":"arxiv","version":4}},"canonical_sha256":"e5b49d64706537e9df7eed88a33423dc278c1430d75ba807f33d9c8de00dbd25","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e5b49d64706537e9df7eed88a33423dc278c1430d75ba807f33d9c8de00dbd25","first_computed_at":"2026-07-05T09:29:26.514904Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:29:26.514904Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YfxX4/TQ4/9UOZHMvJuK1ZJvr5x9F7nKY1bgXVVlN4aLoy9BjN+5SGobDXkr3+Bk6DQfCQKdUi1dL4kXQ6Z5Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:29:26.515400Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.17946","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:98657b61b491e34fdbe64336870505862d19baf23f4b7d2b44a6c24aa915fafc","sha256:b7a659c27adbd44f03d660194bf7a4fc32f5f175d576ff4f2d8f67bee32049f7"],"state_sha256":"704065bb54b92339c34a0219c268754fe5db0a6f187cf74291aafe365a75d40e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4q2rjAg4fGHyE3QY6GMXnBVV1dDTMbEYeZlUgT21r05jxgmsi6B8xGy2ivw2l3EuFyA8YtktjHod1/0RPs+6Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T13:56:23.260788Z","bundle_sha256":"c77bc5d7a3a28bf4ac03841e0f9f9f0cc0469f1fb769f99cf421edd73e2b17a6"}}