{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6OUR5AALF5WESPLWICBBL4T6LH","short_pith_number":"pith:6OUR5AAL","canonical_record":{"source":{"id":"2008.05000","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-11T20:53:50Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6e4f4afd8e1d1020a30d9b0ce344faba5a022d5208e482a07b52daa268b30ba9","abstract_canon_sha256":"5f33293505614539ab7d38619af92d16d6158f7f139433232e1946b1f1af7fce"},"schema_version":"1.0"},"canonical_sha256":"f3a91e800b2f6c493d76408215f27e59cbf21c803c1e8183ffe7aa4ec874e5bc","source":{"kind":"arxiv","id":"2008.05000","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.05000","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"arxiv_version","alias_value":"2008.05000v3","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.05000","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_12","alias_value":"6OUR5AALF5WE","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_16","alias_value":"6OUR5AALF5WESPLW","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_8","alias_value":"6OUR5AAL","created_at":"2026-07-05T02:22:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6OUR5AALF5WESPLWICBBL4T6LH","target":"record","payload":{"canonical_record":{"source":{"id":"2008.05000","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-11T20:53:50Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6e4f4afd8e1d1020a30d9b0ce344faba5a022d5208e482a07b52daa268b30ba9","abstract_canon_sha256":"5f33293505614539ab7d38619af92d16d6158f7f139433232e1946b1f1af7fce"},"schema_version":"1.0"},"canonical_sha256":"f3a91e800b2f6c493d76408215f27e59cbf21c803c1e8183ffe7aa4ec874e5bc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:22:56.835777Z","signature_b64":"IyDXN4aMQcs1t63FDuQ7R8UUKHMXwCYdT/cjJLEbD5IcI5zofvWXxQ0O/tp+UYiMkh+2+unwZE1qHDKb37dGAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3a91e800b2f6c493d76408215f27e59cbf21c803c1e8183ffe7aa4ec874e5bc","last_reissued_at":"2026-07-05T02:22:56.835334Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:22:56.835334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.05000","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:22:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+nFiaE7XzXdPtoX/kBzpx94vRJpHt7NZJm44wc2URRVqjC5VBi+c4dx505zCKcxcz77e9Zgmd5aEDG25jttMCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T21:09:23.795069Z"},"content_sha256":"48235b8fd403ee30983ab3adbf1206c4e8217703913efe4a3b4954082675635f","schema_version":"1.0","event_id":"sha256:48235b8fd403ee30983ab3adbf1206c4e8217703913efe4a3b4954082675635f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6OUR5AALF5WESPLWICBBL4T6LH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Degree-Quant: Quantization-Aware Training for Graph Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Javier Fernandez-Marques, Nicholas D. Lane, Shyam A. Tailor","submitted_at":"2020-08-11T20:53:50Z","abstract_excerpt":"Graph neural networks (GNNs) have demonstrated strong performance on a wide variety of tasks due to their ability to model non-uniform structured data. Despite their promise, there exists little research exploring methods to make them more efficient at inference time. In this work, we explore the viability of training quantized GNNs, enabling the usage of low precision integer arithmetic during inference. We identify the sources of error that uniquely arise when attempting to quantize GNNs, and propose an architecturally-agnostic method, Degree-Quant, to improve performance over existing quant"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.05000","kind":"arxiv","version":3},"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/2008.05000/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":"2026-07-05T02:22:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yb2ZIyzya18oTqsZuONjIx2xLQTuW53AqgGLVIuJYmxpIS3+qxAInajZRoqCnlcgBfk1CG82BTUiikblZ4CdAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T21:09:23.795728Z"},"content_sha256":"f97bb3575d82f740769d4e010a772abdf95c8ed5d99696a65539fab462c631f2","schema_version":"1.0","event_id":"sha256:f97bb3575d82f740769d4e010a772abdf95c8ed5d99696a65539fab462c631f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6OUR5AALF5WESPLWICBBL4T6LH/bundle.json","state_url":"https://pith.science/pith/6OUR5AALF5WESPLWICBBL4T6LH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6OUR5AALF5WESPLWICBBL4T6LH/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":"2026-08-19T21:09:23Z","links":{"resolver":"https://pith.science/pith/6OUR5AALF5WESPLWICBBL4T6LH","bundle":"https://pith.science/pith/6OUR5AALF5WESPLWICBBL4T6LH/bundle.json","state":"https://pith.science/pith/6OUR5AALF5WESPLWICBBL4T6LH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6OUR5AALF5WESPLWICBBL4T6LH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6OUR5AALF5WESPLWICBBL4T6LH","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":"5f33293505614539ab7d38619af92d16d6158f7f139433232e1946b1f1af7fce","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-11T20:53:50Z","title_canon_sha256":"6e4f4afd8e1d1020a30d9b0ce344faba5a022d5208e482a07b52daa268b30ba9"},"schema_version":"1.0","source":{"id":"2008.05000","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.05000","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"arxiv_version","alias_value":"2008.05000v3","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.05000","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_12","alias_value":"6OUR5AALF5WE","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_16","alias_value":"6OUR5AALF5WESPLW","created_at":"2026-07-05T02:22:56Z"},{"alias_kind":"pith_short_8","alias_value":"6OUR5AAL","created_at":"2026-07-05T02:22:56Z"}],"graph_snapshots":[{"event_id":"sha256:f97bb3575d82f740769d4e010a772abdf95c8ed5d99696a65539fab462c631f2","target":"graph","created_at":"2026-07-05T02:22:56Z","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/2008.05000/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph neural networks (GNNs) have demonstrated strong performance on a wide variety of tasks due to their ability to model non-uniform structured data. Despite their promise, there exists little research exploring methods to make them more efficient at inference time. In this work, we explore the viability of training quantized GNNs, enabling the usage of low precision integer arithmetic during inference. We identify the sources of error that uniquely arise when attempting to quantize GNNs, and propose an architecturally-agnostic method, Degree-Quant, to improve performance over existing quant","authors_text":"Javier Fernandez-Marques, Nicholas D. Lane, Shyam A. Tailor","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-11T20:53:50Z","title":"Degree-Quant: Quantization-Aware Training for Graph Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.05000","kind":"arxiv","version":3},"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":"sha256:48235b8fd403ee30983ab3adbf1206c4e8217703913efe4a3b4954082675635f","target":"record","created_at":"2026-07-05T02:22:56Z","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":"5f33293505614539ab7d38619af92d16d6158f7f139433232e1946b1f1af7fce","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-11T20:53:50Z","title_canon_sha256":"6e4f4afd8e1d1020a30d9b0ce344faba5a022d5208e482a07b52daa268b30ba9"},"schema_version":"1.0","source":{"id":"2008.05000","kind":"arxiv","version":3}},"canonical_sha256":"f3a91e800b2f6c493d76408215f27e59cbf21c803c1e8183ffe7aa4ec874e5bc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3a91e800b2f6c493d76408215f27e59cbf21c803c1e8183ffe7aa4ec874e5bc","first_computed_at":"2026-07-05T02:22:56.835334Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:22:56.835334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IyDXN4aMQcs1t63FDuQ7R8UUKHMXwCYdT/cjJLEbD5IcI5zofvWXxQ0O/tp+UYiMkh+2+unwZE1qHDKb37dGAg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:22:56.835777Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.05000","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48235b8fd403ee30983ab3adbf1206c4e8217703913efe4a3b4954082675635f","sha256:f97bb3575d82f740769d4e010a772abdf95c8ed5d99696a65539fab462c631f2"],"state_sha256":"569a392eb52f4cf27f9678e8253285303942bba54a135cbfdd7ee712b9c773f2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PjnGFliGtYdps7gmk8mXwdYH3IiCxZu3rVT2uaVOfVc1d2+Ei6EGAqnI95j9E0VCehITowoodok0bExrg7W1BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T21:09:23.831342Z","bundle_sha256":"841529b02a27b783a75c7d3974521ebc12d244bd27c407dab1ca948cabc0c6a0"}}