{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:7CWWBWY7PNSNPWYIHRR2C4YQ7Y","short_pith_number":"pith:7CWWBWY7","canonical_record":{"source":{"id":"2507.11953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:39:11Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e8cf59079823320350743a580fcb851e57ec697a1c05d1b80dee80d19a5abdba","abstract_canon_sha256":"7b430eac0700f5c0b55124224b6118df44fb5f065de174e567fafa25fb6762b0"},"schema_version":"1.0"},"canonical_sha256":"f8ad60db1f7b64d7db083c63a17310fe34ed3db42bd5a8b26da69190bdc2aef5","source":{"kind":"arxiv","id":"2507.11953","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.11953","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"arxiv_version","alias_value":"2507.11953v1","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11953","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_12","alias_value":"7CWWBWY7PNSN","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_16","alias_value":"7CWWBWY7PNSNPWYI","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_8","alias_value":"7CWWBWY7","created_at":"2026-07-05T11:38:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:7CWWBWY7PNSNPWYIHRR2C4YQ7Y","target":"record","payload":{"canonical_record":{"source":{"id":"2507.11953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:39:11Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e8cf59079823320350743a580fcb851e57ec697a1c05d1b80dee80d19a5abdba","abstract_canon_sha256":"7b430eac0700f5c0b55124224b6118df44fb5f065de174e567fafa25fb6762b0"},"schema_version":"1.0"},"canonical_sha256":"f8ad60db1f7b64d7db083c63a17310fe34ed3db42bd5a8b26da69190bdc2aef5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:11.416308Z","signature_b64":"+g54Ztr4OEFfid32iS0zEpRFc0YLp9llOTA4ocFmgX0hroVxur2svKtsPPvQVZR5xlNNHmLSBcglUZnXQpXWCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f8ad60db1f7b64d7db083c63a17310fe34ed3db42bd5a8b26da69190bdc2aef5","last_reissued_at":"2026-07-05T11:38:11.415796Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:11.415796Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.11953","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":"2026-07-05T11:38:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uaHyG1Cc7gf2XijaAqon9nH7ozA3L4lnhcWNuVNGXbHeHp3ETuTwXhURnS6rEsH+ZkbFPOpoASPBORqZx71mDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T22:56:26.565966Z"},"content_sha256":"cc5d4bb9d42ebaaa3f576674ccf80e1a8bcdc6b687064ec8295d700786588227","schema_version":"1.0","event_id":"sha256:cc5d4bb9d42ebaaa3f576674ccf80e1a8bcdc6b687064ec8295d700786588227"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:7CWWBWY7PNSNPWYIHRR2C4YQ7Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IAM: Efficient Inference through Attention Mapping between Different-scale LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Hai Zhao, Yi Zhao, Zuchao Li","submitted_at":"2025-07-16T06:39:11Z","abstract_excerpt":"LLMs encounter significant challenges in resource consumption nowadays, especially with long contexts. Despite extensive efforts dedicate to enhancing inference efficiency, these methods primarily exploit internal sparsity within the models, without leveraging external information for optimization. We identify the high similarity of attention matrices across different-scale LLMs, which offers a novel perspective for optimization. We first conduct a comprehensive analysis of how to measure similarity, how to select mapping Layers and whether mapping is consistency. Based on these insights, we i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11953","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/2507.11953/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":"2026-07-05T11:38:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9fhljsQtcp6ZSmnSnnYv/PvrQ4uLcWTJ+PkkBtCZH9TAq3ZpCYMlwRGORwM7xVaowXc9v8hddj9Ek6cFkxfWDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T22:56:26.566448Z"},"content_sha256":"354d10cd48e2a5c9cc62cd0a15365490f5c82eb983cfc95aee595fbf79d78ea2","schema_version":"1.0","event_id":"sha256:354d10cd48e2a5c9cc62cd0a15365490f5c82eb983cfc95aee595fbf79d78ea2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/bundle.json","state_url":"https://pith.science/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/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":"2026-08-06T22:56:26Z","links":{"resolver":"https://pith.science/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y","bundle":"https://pith.science/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/bundle.json","state":"https://pith.science/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7CWWBWY7PNSNPWYIHRR2C4YQ7Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:7CWWBWY7PNSNPWYIHRR2C4YQ7Y","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":"7b430eac0700f5c0b55124224b6118df44fb5f065de174e567fafa25fb6762b0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:39:11Z","title_canon_sha256":"e8cf59079823320350743a580fcb851e57ec697a1c05d1b80dee80d19a5abdba"},"schema_version":"1.0","source":{"id":"2507.11953","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.11953","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"arxiv_version","alias_value":"2507.11953v1","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11953","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_12","alias_value":"7CWWBWY7PNSN","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_16","alias_value":"7CWWBWY7PNSNPWYI","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_8","alias_value":"7CWWBWY7","created_at":"2026-07-05T11:38:11Z"}],"graph_snapshots":[{"event_id":"sha256:354d10cd48e2a5c9cc62cd0a15365490f5c82eb983cfc95aee595fbf79d78ea2","target":"graph","created_at":"2026-07-05T11:38:11Z","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/2507.11953/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"LLMs encounter significant challenges in resource consumption nowadays, especially with long contexts. Despite extensive efforts dedicate to enhancing inference efficiency, these methods primarily exploit internal sparsity within the models, without leveraging external information for optimization. We identify the high similarity of attention matrices across different-scale LLMs, which offers a novel perspective for optimization. We first conduct a comprehensive analysis of how to measure similarity, how to select mapping Layers and whether mapping is consistency. Based on these insights, we i","authors_text":"Hai Zhao, Yi Zhao, Zuchao Li","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:39:11Z","title":"IAM: Efficient Inference through Attention Mapping between Different-scale LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11953","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:cc5d4bb9d42ebaaa3f576674ccf80e1a8bcdc6b687064ec8295d700786588227","target":"record","created_at":"2026-07-05T11:38:11Z","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":"7b430eac0700f5c0b55124224b6118df44fb5f065de174e567fafa25fb6762b0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:39:11Z","title_canon_sha256":"e8cf59079823320350743a580fcb851e57ec697a1c05d1b80dee80d19a5abdba"},"schema_version":"1.0","source":{"id":"2507.11953","kind":"arxiv","version":1}},"canonical_sha256":"f8ad60db1f7b64d7db083c63a17310fe34ed3db42bd5a8b26da69190bdc2aef5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f8ad60db1f7b64d7db083c63a17310fe34ed3db42bd5a8b26da69190bdc2aef5","first_computed_at":"2026-07-05T11:38:11.415796Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:38:11.415796Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+g54Ztr4OEFfid32iS0zEpRFc0YLp9llOTA4ocFmgX0hroVxur2svKtsPPvQVZR5xlNNHmLSBcglUZnXQpXWCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:38:11.416308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.11953","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc5d4bb9d42ebaaa3f576674ccf80e1a8bcdc6b687064ec8295d700786588227","sha256:354d10cd48e2a5c9cc62cd0a15365490f5c82eb983cfc95aee595fbf79d78ea2"],"state_sha256":"0cf9d8744e091dd36f8c3dee6d713c380a9b02e351b1924ca5e8e7bf57ace6d7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K/3QbzayZYwHK7qOFoYQXQJ7oMxS0t55HoYhKk3/tQIyZHxKVQ6NCtV1dYs+MJ35ibcds3y5SmIlBmbNH8GeBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T22:56:26.569939Z","bundle_sha256":"2c77b5317f991db680643f549454c1f2c108ec93fac59b9d88ce23ebcd592fe8"}}