{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:K7SMXBUONCYS7EC2SZZ4OOTUNG","short_pith_number":"pith:K7SMXBUO","canonical_record":{"source":{"id":"2304.14698","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-04-28T09:06:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"aacdc8aa1d8687b17d022baaf9e7af3ff6acbda1fb4cf6f8d352b783a3d65e54","abstract_canon_sha256":"b2134f2fe3ff2248cba0dfb53e991165e2fcba3ea273566c6a36b126d7845db6"},"schema_version":"1.0"},"canonical_sha256":"57e4cb868e68b12f905a9673c73a7469ad069946d343df96e8112d40230536bd","source":{"kind":"arxiv","id":"2304.14698","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.14698","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"2304.14698v1","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.14698","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"K7SMXBUONCYS","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_16","alias_value":"K7SMXBUONCYS7EC2","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_8","alias_value":"K7SMXBUO","created_at":"2026-07-05T06:05:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:K7SMXBUONCYS7EC2SZZ4OOTUNG","target":"record","payload":{"canonical_record":{"source":{"id":"2304.14698","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-04-28T09:06:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"aacdc8aa1d8687b17d022baaf9e7af3ff6acbda1fb4cf6f8d352b783a3d65e54","abstract_canon_sha256":"b2134f2fe3ff2248cba0dfb53e991165e2fcba3ea273566c6a36b126d7845db6"},"schema_version":"1.0"},"canonical_sha256":"57e4cb868e68b12f905a9673c73a7469ad069946d343df96e8112d40230536bd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:05:20.184720Z","signature_b64":"Vw/WwNMoY9GiUcRiWm/Bm7bmZ6DhRP/PgqFxp1m89PCzGwQVdFSZhWNoXDVc9v/I71RcdHkdEQh+IpA54YE7BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57e4cb868e68b12f905a9673c73a7469ad069946d343df96e8112d40230536bd","last_reissued_at":"2026-07-05T06:05:20.184299Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:05:20.184299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.14698","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":"2026-07-05T06:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qqpvnfgRtJzDPPdSLrnC3Sq10JIqwSs1gI9ecw/QffG9ysvF7iOtCIgwD2ZD/fbLVeE6hJAawb8dJQtkG+AUCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:13:24.382802Z"},"content_sha256":"a261add56be31b2261641b00921b509a49e507765927d4de4097fae1c1d8373b","schema_version":"1.0","event_id":"sha256:a261add56be31b2261641b00921b509a49e507765927d4de4097fae1c1d8373b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:K7SMXBUONCYS7EC2SZZ4OOTUNG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Eiko Yoneki, Guoliang He, Sean Parker","submitted_at":"2023-04-28T09:06:18Z","abstract_excerpt":"Tensor graph superoptimisation systems perform a sequence of subgraph substitution to neural networks, to find the optimal computation graph structure. Such a graph transformation process naturally falls into the framework of sequential decision-making, and existing systems typically employ a greedy search approach, which cannot explore the whole search space as it cannot tolerate a temporary loss of performance. In this paper, we address the tensor graph superoptimisation problem by exploring an alternative search approach, reinforcement learning (RL). Our proposed approach, X-RLflow, can lea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.14698","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/2304.14698/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":"2026-07-05T06:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Sh3KHfZkB4fV0xBucxcXSL6b1fhp27bQ8OR46/UIiRTQXjvWjY98ClmL45PShoTY4agQ6+/M3Dcy/2QRQ+RCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:13:24.383559Z"},"content_sha256":"427af68c1acbd1c0e9dcf62d6b60418882e3fa8e1da21d77eb0ae95b1d435f7d","schema_version":"1.0","event_id":"sha256:427af68c1acbd1c0e9dcf62d6b60418882e3fa8e1da21d77eb0ae95b1d435f7d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/bundle.json","state_url":"https://pith.science/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/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":"2026-08-09T13:13:24Z","links":{"resolver":"https://pith.science/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG","bundle":"https://pith.science/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/bundle.json","state":"https://pith.science/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K7SMXBUONCYS7EC2SZZ4OOTUNG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:K7SMXBUONCYS7EC2SZZ4OOTUNG","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":"b2134f2fe3ff2248cba0dfb53e991165e2fcba3ea273566c6a36b126d7845db6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-04-28T09:06:18Z","title_canon_sha256":"aacdc8aa1d8687b17d022baaf9e7af3ff6acbda1fb4cf6f8d352b783a3d65e54"},"schema_version":"1.0","source":{"id":"2304.14698","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.14698","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"2304.14698v1","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.14698","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"K7SMXBUONCYS","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_16","alias_value":"K7SMXBUONCYS7EC2","created_at":"2026-07-05T06:05:20Z"},{"alias_kind":"pith_short_8","alias_value":"K7SMXBUO","created_at":"2026-07-05T06:05:20Z"}],"graph_snapshots":[{"event_id":"sha256:427af68c1acbd1c0e9dcf62d6b60418882e3fa8e1da21d77eb0ae95b1d435f7d","target":"graph","created_at":"2026-07-05T06:05:20Z","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/2304.14698/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Tensor graph superoptimisation systems perform a sequence of subgraph substitution to neural networks, to find the optimal computation graph structure. Such a graph transformation process naturally falls into the framework of sequential decision-making, and existing systems typically employ a greedy search approach, which cannot explore the whole search space as it cannot tolerate a temporary loss of performance. In this paper, we address the tensor graph superoptimisation problem by exploring an alternative search approach, reinforcement learning (RL). Our proposed approach, X-RLflow, can lea","authors_text":"Eiko Yoneki, Guoliang He, Sean Parker","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-04-28T09:06:18Z","title":"X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.14698","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:a261add56be31b2261641b00921b509a49e507765927d4de4097fae1c1d8373b","target":"record","created_at":"2026-07-05T06:05:20Z","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":"b2134f2fe3ff2248cba0dfb53e991165e2fcba3ea273566c6a36b126d7845db6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-04-28T09:06:18Z","title_canon_sha256":"aacdc8aa1d8687b17d022baaf9e7af3ff6acbda1fb4cf6f8d352b783a3d65e54"},"schema_version":"1.0","source":{"id":"2304.14698","kind":"arxiv","version":1}},"canonical_sha256":"57e4cb868e68b12f905a9673c73a7469ad069946d343df96e8112d40230536bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57e4cb868e68b12f905a9673c73a7469ad069946d343df96e8112d40230536bd","first_computed_at":"2026-07-05T06:05:20.184299Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:05:20.184299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vw/WwNMoY9GiUcRiWm/Bm7bmZ6DhRP/PgqFxp1m89PCzGwQVdFSZhWNoXDVc9v/I71RcdHkdEQh+IpA54YE7BA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:05:20.184720Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.14698","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a261add56be31b2261641b00921b509a49e507765927d4de4097fae1c1d8373b","sha256:427af68c1acbd1c0e9dcf62d6b60418882e3fa8e1da21d77eb0ae95b1d435f7d"],"state_sha256":"d049fd2607cd91de3acdb6483dd3e4ef0a3cd283b44e48387463aceb7e9e64dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"97/77AHFENJTyj5p76R3nuHdo15YTjTUyJ/SatPByEBxosPyqWgPq+wzX+5VJi3GktiAG+fu2f2fO/0w+6ffCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:13:24.390784Z","bundle_sha256":"c92585f8227cac52588ba756d141b840f61083f857275b1eb423c96254e0fd81"}}