{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:3EAXOSH56K6RC5QW46ZYRBBQSK","short_pith_number":"pith:3EAXOSH5","canonical_record":{"source":{"id":"2410.17397","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-10-22T20:12:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"d6ad4c2ac3e1f583cbb0aa14707e7033cf569f8bd0a40564b241340be34d6317","abstract_canon_sha256":"f09aafdf05c1ec1432bc859a09cff8da2c30268d2fd7a190f1621b723d6d952c"},"schema_version":"1.0"},"canonical_sha256":"d9017748fdf2bd117616e7b388843092a23ee47517220215b6f0fc1c83eff0b9","source":{"kind":"arxiv","id":"2410.17397","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.17397","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"arxiv_version","alias_value":"2410.17397v1","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.17397","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_12","alias_value":"3EAXOSH56K6R","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_16","alias_value":"3EAXOSH56K6RC5QW","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_8","alias_value":"3EAXOSH5","created_at":"2026-07-05T09:24:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:3EAXOSH56K6RC5QW46ZYRBBQSK","target":"record","payload":{"canonical_record":{"source":{"id":"2410.17397","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-10-22T20:12:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"d6ad4c2ac3e1f583cbb0aa14707e7033cf569f8bd0a40564b241340be34d6317","abstract_canon_sha256":"f09aafdf05c1ec1432bc859a09cff8da2c30268d2fd7a190f1621b723d6d952c"},"schema_version":"1.0"},"canonical_sha256":"d9017748fdf2bd117616e7b388843092a23ee47517220215b6f0fc1c83eff0b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:24:21.609018Z","signature_b64":"1RDtYfouDwRqj02ZnTI58wLLDgAaecTrW5E77JqfTnFyJbRIUuDKaBhKMZ+3uyvUUNkAno+lthNJKxeJccZcCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d9017748fdf2bd117616e7b388843092a23ee47517220215b6f0fc1c83eff0b9","last_reissued_at":"2026-07-05T09:24:21.608525Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:24:21.608525Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.17397","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":"2026-07-05T09:24:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1PGUkwqlPykXftUPj45Ao35Xn7VeyFw3j3vW7Ru7qaqoT4jL4/BfrolbFRdifoa023EgR4E0muYi0FIpcQ6rBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:12:33.387546Z"},"content_sha256":"de07d4cc047a19297e06b6cf1c853ded12e68287b0d5c064ad90e64882fd0f3f","schema_version":"1.0","event_id":"sha256:de07d4cc047a19297e06b6cf1c853ded12e68287b0d5c064ad90e64882fd0f3f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:3EAXOSH56K6RC5QW46ZYRBBQSK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantum Large Language Models via Tensor Network Disentanglers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"quant-ph","authors_text":"Borja Aizpurua, Roman Orus, Saeed S. Jahromi, Sukhbinder Singh","submitted_at":"2024-10-22T20:12:04Z","abstract_excerpt":"We propose a method to enhance the performance of Large Language Models (LLMs) by integrating quantum computing and quantum-inspired techniques. Specifically, our approach involves replacing the weight matrices in the Self-Attention and Multi-layer Perceptron layers with a combination of two variational quantum circuits and a quantum-inspired tensor network, such as a Matrix Product Operator (MPO). This substitution enables the reproduction of classical LLM functionality by decomposing weight matrices through the application of tensor network disentanglers and MPOs, leveraging well-established"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.17397","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/2410.17397/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":"2026-07-05T09:24:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LYYF4E2zNfuzSHuMjcebbi2uTPzVajedoi/omI+nyFoOlDVpZofuGeIjrtj8Zfo2Wdgb9+QJHiZAH6EnsDctDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:12:33.388877Z"},"content_sha256":"41badf8612133b5df64d3765d3fdc67db5bd28aa77c86bdda0826a57ebf879d4","schema_version":"1.0","event_id":"sha256:41badf8612133b5df64d3765d3fdc67db5bd28aa77c86bdda0826a57ebf879d4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/bundle.json","state_url":"https://pith.science/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/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":"2026-08-16T21:12:33Z","links":{"resolver":"https://pith.science/pith/3EAXOSH56K6RC5QW46ZYRBBQSK","bundle":"https://pith.science/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/bundle.json","state":"https://pith.science/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3EAXOSH56K6RC5QW46ZYRBBQSK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3EAXOSH56K6RC5QW46ZYRBBQSK","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":"f09aafdf05c1ec1432bc859a09cff8da2c30268d2fd7a190f1621b723d6d952c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-10-22T20:12:04Z","title_canon_sha256":"d6ad4c2ac3e1f583cbb0aa14707e7033cf569f8bd0a40564b241340be34d6317"},"schema_version":"1.0","source":{"id":"2410.17397","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.17397","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"arxiv_version","alias_value":"2410.17397v1","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.17397","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_12","alias_value":"3EAXOSH56K6R","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_16","alias_value":"3EAXOSH56K6RC5QW","created_at":"2026-07-05T09:24:21Z"},{"alias_kind":"pith_short_8","alias_value":"3EAXOSH5","created_at":"2026-07-05T09:24:21Z"}],"graph_snapshots":[{"event_id":"sha256:41badf8612133b5df64d3765d3fdc67db5bd28aa77c86bdda0826a57ebf879d4","target":"graph","created_at":"2026-07-05T09:24:21Z","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/2410.17397/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a method to enhance the performance of Large Language Models (LLMs) by integrating quantum computing and quantum-inspired techniques. Specifically, our approach involves replacing the weight matrices in the Self-Attention and Multi-layer Perceptron layers with a combination of two variational quantum circuits and a quantum-inspired tensor network, such as a Matrix Product Operator (MPO). This substitution enables the reproduction of classical LLM functionality by decomposing weight matrices through the application of tensor network disentanglers and MPOs, leveraging well-established","authors_text":"Borja Aizpurua, Roman Orus, Saeed S. Jahromi, Sukhbinder Singh","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-10-22T20:12:04Z","title":"Quantum Large Language Models via Tensor Network Disentanglers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.17397","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:de07d4cc047a19297e06b6cf1c853ded12e68287b0d5c064ad90e64882fd0f3f","target":"record","created_at":"2026-07-05T09:24:21Z","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":"f09aafdf05c1ec1432bc859a09cff8da2c30268d2fd7a190f1621b723d6d952c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-10-22T20:12:04Z","title_canon_sha256":"d6ad4c2ac3e1f583cbb0aa14707e7033cf569f8bd0a40564b241340be34d6317"},"schema_version":"1.0","source":{"id":"2410.17397","kind":"arxiv","version":1}},"canonical_sha256":"d9017748fdf2bd117616e7b388843092a23ee47517220215b6f0fc1c83eff0b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d9017748fdf2bd117616e7b388843092a23ee47517220215b6f0fc1c83eff0b9","first_computed_at":"2026-07-05T09:24:21.608525Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:24:21.608525Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1RDtYfouDwRqj02ZnTI58wLLDgAaecTrW5E77JqfTnFyJbRIUuDKaBhKMZ+3uyvUUNkAno+lthNJKxeJccZcCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:24:21.609018Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.17397","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de07d4cc047a19297e06b6cf1c853ded12e68287b0d5c064ad90e64882fd0f3f","sha256:41badf8612133b5df64d3765d3fdc67db5bd28aa77c86bdda0826a57ebf879d4"],"state_sha256":"c51b3d1cfd1db3bd8038a40a76b89e89e18aa679a9da6ac256f9d17621dc82eb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OymGScPJB+cRXocksp24eu7ng8zH2hxvFs/w6tEFfFTW3u0c6xastrMBC2VY0m1Vk19EdP1+M1CrDdg8EdqXCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T21:12:33.394796Z","bundle_sha256":"db62db60b97f205e440be56016017c78d1bc65d933bd55bc48d6891ae3736614"}}