{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XXRJL7ECTBPQX2BXTJW354FYYP","short_pith_number":"pith:XXRJL7EC","canonical_record":{"source":{"id":"2412.01380","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T11:07:51Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"426682f05831c36fe361e561f9b5c66b7478a3533e2eba97855dffd0fcbddad4","abstract_canon_sha256":"15da05e1e143d692480890fcee92b26068ca73e5834a2858c552f850192c99e0"},"schema_version":"1.0"},"canonical_sha256":"bde295fc82985f0be8379a6dbef0b8c3c1232ad5933e0f3699f9ab1e8f882c3d","source":{"kind":"arxiv","id":"2412.01380","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01380","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01380v2","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01380","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_12","alias_value":"XXRJL7ECTBPQ","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_16","alias_value":"XXRJL7ECTBPQX2BX","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_8","alias_value":"XXRJL7EC","created_at":"2026-07-05T10:43:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XXRJL7ECTBPQX2BXTJW354FYYP","target":"record","payload":{"canonical_record":{"source":{"id":"2412.01380","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T11:07:51Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"426682f05831c36fe361e561f9b5c66b7478a3533e2eba97855dffd0fcbddad4","abstract_canon_sha256":"15da05e1e143d692480890fcee92b26068ca73e5834a2858c552f850192c99e0"},"schema_version":"1.0"},"canonical_sha256":"bde295fc82985f0be8379a6dbef0b8c3c1232ad5933e0f3699f9ab1e8f882c3d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:43:41.386302Z","signature_b64":"Goy2BEI9NgOarm2ewE7+maxXFY7/VXP9wb8K82kYnR3AEpk9DTQzrQZCDuiXiZAke/dVchpEaaloX7Jxg1bgAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bde295fc82985f0be8379a6dbef0b8c3c1232ad5933e0f3699f9ab1e8f882c3d","last_reissued_at":"2026-07-05T10:43:41.385818Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:43:41.385818Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.01380","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":"2026-07-05T10:43:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GY/Wfl91NqStJxPIdq5w/aYavoMWugqzbQXXab2sRDosUBPHnDPMSCObf7aAls3eqa5Qcma0aY17wdt6ZkbzAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:35:47.530394Z"},"content_sha256":"1109b9397755a2a136bc709fca61f0a9386e934f36aed903c88026d1ae94d9e8","schema_version":"1.0","event_id":"sha256:1109b9397755a2a136bc709fca61f0a9386e934f36aed903c88026d1ae94d9e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XXRJL7ECTBPQX2BXTJW354FYYP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Amir Jalalirad, Andrii Skliar, Bence Major, Davide Belli, Marco Federici, Markus Nagel, Mart van Baalen, Paul Whatmough","submitted_at":"2024-12-02T11:07:51Z","abstract_excerpt":"While mobile devices provide ever more compute power, improvements in DRAM bandwidth are much slower. This is unfortunate for large language model (LLM) token generation, which is heavily memory-bound. Previous work has proposed to leverage natural dynamic activation sparsity in ReLU-activated LLMs to reduce effective DRAM bandwidth per token. However, more recent LLMs use SwiGLU instead of ReLU, which results in little inherent sparsity. While SwiGLU activations can be pruned based on magnitude, the resulting sparsity patterns are difficult to predict, rendering previous approaches ineffectiv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01380","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/2412.01380/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":"2026-07-05T10:43:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Li3vAkpUU4jCExyNa9w4zmybz+Ob/eqCgbDp9LFbXSnxJk2REdxnUG4goDAHuNP/5WDo1OBQBSOHifEwLAynBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:35:47.531356Z"},"content_sha256":"b328c5644a8e355c0bdd8fed20a251fda8115f85ebea84f7b1978e32688f9c5a","schema_version":"1.0","event_id":"sha256:b328c5644a8e355c0bdd8fed20a251fda8115f85ebea84f7b1978e32688f9c5a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XXRJL7ECTBPQX2BXTJW354FYYP/bundle.json","state_url":"https://pith.science/pith/XXRJL7ECTBPQX2BXTJW354FYYP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XXRJL7ECTBPQX2BXTJW354FYYP/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":"2026-08-09T16:35:47Z","links":{"resolver":"https://pith.science/pith/XXRJL7ECTBPQX2BXTJW354FYYP","bundle":"https://pith.science/pith/XXRJL7ECTBPQX2BXTJW354FYYP/bundle.json","state":"https://pith.science/pith/XXRJL7ECTBPQX2BXTJW354FYYP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XXRJL7ECTBPQX2BXTJW354FYYP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XXRJL7ECTBPQX2BXTJW354FYYP","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":"15da05e1e143d692480890fcee92b26068ca73e5834a2858c552f850192c99e0","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T11:07:51Z","title_canon_sha256":"426682f05831c36fe361e561f9b5c66b7478a3533e2eba97855dffd0fcbddad4"},"schema_version":"1.0","source":{"id":"2412.01380","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01380","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01380v2","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01380","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_12","alias_value":"XXRJL7ECTBPQ","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_16","alias_value":"XXRJL7ECTBPQX2BX","created_at":"2026-07-05T10:43:41Z"},{"alias_kind":"pith_short_8","alias_value":"XXRJL7EC","created_at":"2026-07-05T10:43:41Z"}],"graph_snapshots":[{"event_id":"sha256:b328c5644a8e355c0bdd8fed20a251fda8115f85ebea84f7b1978e32688f9c5a","target":"graph","created_at":"2026-07-05T10:43:41Z","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/2412.01380/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While mobile devices provide ever more compute power, improvements in DRAM bandwidth are much slower. This is unfortunate for large language model (LLM) token generation, which is heavily memory-bound. Previous work has proposed to leverage natural dynamic activation sparsity in ReLU-activated LLMs to reduce effective DRAM bandwidth per token. However, more recent LLMs use SwiGLU instead of ReLU, which results in little inherent sparsity. While SwiGLU activations can be pruned based on magnitude, the resulting sparsity patterns are difficult to predict, rendering previous approaches ineffectiv","authors_text":"Amir Jalalirad, Andrii Skliar, Bence Major, Davide Belli, Marco Federici, Markus Nagel, Mart van Baalen, Paul Whatmough","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T11:07:51Z","title":"Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01380","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":"sha256:1109b9397755a2a136bc709fca61f0a9386e934f36aed903c88026d1ae94d9e8","target":"record","created_at":"2026-07-05T10:43:41Z","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":"15da05e1e143d692480890fcee92b26068ca73e5834a2858c552f850192c99e0","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T11:07:51Z","title_canon_sha256":"426682f05831c36fe361e561f9b5c66b7478a3533e2eba97855dffd0fcbddad4"},"schema_version":"1.0","source":{"id":"2412.01380","kind":"arxiv","version":2}},"canonical_sha256":"bde295fc82985f0be8379a6dbef0b8c3c1232ad5933e0f3699f9ab1e8f882c3d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bde295fc82985f0be8379a6dbef0b8c3c1232ad5933e0f3699f9ab1e8f882c3d","first_computed_at":"2026-07-05T10:43:41.385818Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:43:41.385818Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Goy2BEI9NgOarm2ewE7+maxXFY7/VXP9wb8K82kYnR3AEpk9DTQzrQZCDuiXiZAke/dVchpEaaloX7Jxg1bgAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:43:41.386302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.01380","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1109b9397755a2a136bc709fca61f0a9386e934f36aed903c88026d1ae94d9e8","sha256:b328c5644a8e355c0bdd8fed20a251fda8115f85ebea84f7b1978e32688f9c5a"],"state_sha256":"bb5ee0dc660ba47a874889a37fea759d51c4cd4e62b7ab9454fee6fa1f6f32bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z/54V/no2WSQWuPqeWEk5L09YhN4gDII6YA1YnV5S13nGx2BPL7SbxMf2hq99oZTlkNd5um7sNRNMxvW8s7kDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:35:47.536484Z","bundle_sha256":"ce7f913190ff9b020a349ae285a99494650cb0af8435d6aa82b73d64c0090792"}}