{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:D675ORG5QB72LI63M4QMR3GPCU","short_pith_number":"pith:D675ORG5","canonical_record":{"source":{"id":"2111.05193","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-08T16:55:03Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"edca3105540d24f45af88493ca10738b58291cc74c5b7857ecb2caf2f4e657ba","abstract_canon_sha256":"522c92536944f9bcd2bdb5b517d24a80d926cc0840fa8d279e49fad7cbe4bd7d"},"schema_version":"1.0"},"canonical_sha256":"1fbfd744dd807fa5a3db6720c8eccf1531c32fcf5463b901e1cfd06fefff6ccf","source":{"kind":"arxiv","id":"2111.05193","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.05193","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2111.05193v2","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.05193","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"D675ORG5QB72","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"D675ORG5QB72LI63","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"D675ORG5","created_at":"2026-07-05T03:30:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:D675ORG5QB72LI63M4QMR3GPCU","target":"record","payload":{"canonical_record":{"source":{"id":"2111.05193","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-08T16:55:03Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"edca3105540d24f45af88493ca10738b58291cc74c5b7857ecb2caf2f4e657ba","abstract_canon_sha256":"522c92536944f9bcd2bdb5b517d24a80d926cc0840fa8d279e49fad7cbe4bd7d"},"schema_version":"1.0"},"canonical_sha256":"1fbfd744dd807fa5a3db6720c8eccf1531c32fcf5463b901e1cfd06fefff6ccf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:30:43.092739Z","signature_b64":"78TQLFyex8LVCLM/aPlQGsJbbAjmIWiEqbFKVFcY73V2169uyuSPZBIMdJ0U9svHuWvVMyw65RI1ChZphZPkDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1fbfd744dd807fa5a3db6720c8eccf1531c32fcf5463b901e1cfd06fefff6ccf","last_reissued_at":"2026-07-05T03:30:43.092168Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:30:43.092168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.05193","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":"2026-07-05T03:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cUoqytk1i441YKik2ayejNDi3bDqg4NhXDQpDYfDpGPKiiN0MInPU3/CEqOnVtepGyGQyOQxmnJUHY0NFubLBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T17:42:58.233708Z"},"content_sha256":"08fafc99dd13549c7fcdb47dea3ebe04ec08df6dd6217e2936b4ba8f51d062ed","schema_version":"1.0","event_id":"sha256:08fafc99dd13549c7fcdb47dea3ebe04ec08df6dd6217e2936b4ba8f51d062ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:D675ORG5QB72LI63M4QMR3GPCU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey on Green Deep Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Hao Zhou, Jingjing Xu, Lei Li, Wangchunshu Zhou, Zhiyi Fu","submitted_at":"2021-11-08T16:55:03Z","abstract_excerpt":"In recent years, larger and deeper models are springing up and continuously pushing state-of-the-art (SOTA) results across various fields like natural language processing (NLP) and computer vision (CV). However, despite promising results, it needs to be noted that the computations required by SOTA models have been increased at an exponential rate. Massive computations not only have a surprisingly large carbon footprint but also have negative effects on research inclusiveness and deployment on real-world applications.\n  Green deep learning is an increasingly hot research field that appeals to r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.05193","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/2111.05193/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":"2026-07-05T03:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C7ysXEJ1I25lcWodezs4h+oVIL4Wf/UWWzR5BuhFe3RND5FvwawgWoU/+eNVmHpBIClm2jJGq4THWwTOpCt/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T17:42:58.234368Z"},"content_sha256":"eab22679a5bffd3f1496918d29423377e6d373f727e0bd767522b89e20f1360a","schema_version":"1.0","event_id":"sha256:eab22679a5bffd3f1496918d29423377e6d373f727e0bd767522b89e20f1360a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D675ORG5QB72LI63M4QMR3GPCU/bundle.json","state_url":"https://pith.science/pith/D675ORG5QB72LI63M4QMR3GPCU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D675ORG5QB72LI63M4QMR3GPCU/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":"2026-08-14T17:42:58Z","links":{"resolver":"https://pith.science/pith/D675ORG5QB72LI63M4QMR3GPCU","bundle":"https://pith.science/pith/D675ORG5QB72LI63M4QMR3GPCU/bundle.json","state":"https://pith.science/pith/D675ORG5QB72LI63M4QMR3GPCU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D675ORG5QB72LI63M4QMR3GPCU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:D675ORG5QB72LI63M4QMR3GPCU","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":"522c92536944f9bcd2bdb5b517d24a80d926cc0840fa8d279e49fad7cbe4bd7d","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-08T16:55:03Z","title_canon_sha256":"edca3105540d24f45af88493ca10738b58291cc74c5b7857ecb2caf2f4e657ba"},"schema_version":"1.0","source":{"id":"2111.05193","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.05193","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2111.05193v2","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.05193","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"D675ORG5QB72","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"D675ORG5QB72LI63","created_at":"2026-07-05T03:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"D675ORG5","created_at":"2026-07-05T03:30:43Z"}],"graph_snapshots":[{"event_id":"sha256:eab22679a5bffd3f1496918d29423377e6d373f727e0bd767522b89e20f1360a","target":"graph","created_at":"2026-07-05T03:30:43Z","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/2111.05193/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, larger and deeper models are springing up and continuously pushing state-of-the-art (SOTA) results across various fields like natural language processing (NLP) and computer vision (CV). However, despite promising results, it needs to be noted that the computations required by SOTA models have been increased at an exponential rate. Massive computations not only have a surprisingly large carbon footprint but also have negative effects on research inclusiveness and deployment on real-world applications.\n  Green deep learning is an increasingly hot research field that appeals to r","authors_text":"Hao Zhou, Jingjing Xu, Lei Li, Wangchunshu Zhou, Zhiyi Fu","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-08T16:55:03Z","title":"A Survey on Green Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.05193","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":"sha256:08fafc99dd13549c7fcdb47dea3ebe04ec08df6dd6217e2936b4ba8f51d062ed","target":"record","created_at":"2026-07-05T03:30:43Z","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":"522c92536944f9bcd2bdb5b517d24a80d926cc0840fa8d279e49fad7cbe4bd7d","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-08T16:55:03Z","title_canon_sha256":"edca3105540d24f45af88493ca10738b58291cc74c5b7857ecb2caf2f4e657ba"},"schema_version":"1.0","source":{"id":"2111.05193","kind":"arxiv","version":2}},"canonical_sha256":"1fbfd744dd807fa5a3db6720c8eccf1531c32fcf5463b901e1cfd06fefff6ccf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1fbfd744dd807fa5a3db6720c8eccf1531c32fcf5463b901e1cfd06fefff6ccf","first_computed_at":"2026-07-05T03:30:43.092168Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:30:43.092168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"78TQLFyex8LVCLM/aPlQGsJbbAjmIWiEqbFKVFcY73V2169uyuSPZBIMdJ0U9svHuWvVMyw65RI1ChZphZPkDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:30:43.092739Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.05193","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08fafc99dd13549c7fcdb47dea3ebe04ec08df6dd6217e2936b4ba8f51d062ed","sha256:eab22679a5bffd3f1496918d29423377e6d373f727e0bd767522b89e20f1360a"],"state_sha256":"dc62cdddab15c08b4ed788f7a925609f83dcf895e238d223483ac844ebd79bf6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/YJUsoDJNg96JcaO/yt9pw+H9r2Y7Z7eSHWnFFDde5DQMA/RoPkWX6+TmlqqxzqdCqKzzK82hlmAfDeKHlpTAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T17:42:58.251583Z","bundle_sha256":"00c26e400271efff1e36e03ee3d39f9e443304bb36a999259c0f13b0cd200362"}}