{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:2VBPMM46COKJ3R7LZ47J4ICO32","short_pith_number":"pith:2VBPMM46","canonical_record":{"source":{"id":"2101.01163","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-04T18:54:07Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"acd66d26e97ac440ce4905dea9fa817b68033f2c12b651018d2871ef794bbb6b","abstract_canon_sha256":"6024104fb866d83903b8fcc8039cfd97eb4afb22a8face1d7c65301c46317361"},"schema_version":"1.0"},"canonical_sha256":"d542f6339e13949dc7ebcf3e9e204edebcf4ef2ac29ea0a55de910ac900d4927","source":{"kind":"arxiv","id":"2101.01163","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.01163","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"arxiv_version","alias_value":"2101.01163v2","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.01163","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_12","alias_value":"2VBPMM46COKJ","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_16","alias_value":"2VBPMM46COKJ3R7L","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_8","alias_value":"2VBPMM46","created_at":"2026-07-05T03:43:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:2VBPMM46COKJ3R7LZ47J4ICO32","target":"record","payload":{"canonical_record":{"source":{"id":"2101.01163","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-04T18:54:07Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"acd66d26e97ac440ce4905dea9fa817b68033f2c12b651018d2871ef794bbb6b","abstract_canon_sha256":"6024104fb866d83903b8fcc8039cfd97eb4afb22a8face1d7c65301c46317361"},"schema_version":"1.0"},"canonical_sha256":"d542f6339e13949dc7ebcf3e9e204edebcf4ef2ac29ea0a55de910ac900d4927","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:43:00.950534Z","signature_b64":"Ku2YmkJbRYYvqGf31cvQ1L6pGWqrPRNXUpQRy4IE8WNExfd+04/D0oC3zWKzIucFs6a4NQQu3ILXYFFBEym6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d542f6339e13949dc7ebcf3e9e204edebcf4ef2ac29ea0a55de910ac900d4927","last_reissued_at":"2026-07-05T03:43:00.950032Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:43:00.950032Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.01163","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":"2026-07-05T03:43:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sjvGnVjgsbNff4vcS/BSUrRBqMRsTVDgyGfCMN8vnmjlI8mzMfaP1dGD2mIBCIIsYgZ+DgcPNuwnkl98b0sTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:43:28.692760Z"},"content_sha256":"00948d39633381444da92cb7de36e6334d90e204675b91d47c8fd83a064853a5","schema_version":"1.0","event_id":"sha256:00948d39633381444da92cb7de36e6334d90e204675b91d47c8fd83a064853a5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:2VBPMM46COKJ3R7LZ47J4ICO32","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chaojian Li, Haoran You, Pengfei Xu, Xiaohan Chen, Yang Zhao, Yingyan Lin, Yonggan Fu, Yue Wang, Zhangyang Wang","submitted_at":"2021-01-04T18:54:07Z","abstract_excerpt":"The record-breaking performance of deep neural networks (DNNs) comes with heavy parameterization, leading to external dynamic random-access memory (DRAM) for storage. The prohibitive energy of DRAM accesses makes it non-trivial to deploy DNN on resource-constrained devices, calling for minimizing the weight and data movements to improve the energy efficiency. We present SmartDeal (SD), an algorithm framework to trade higher-cost memory storage/access for lower-cost computation, in order to aggressively boost the storage and energy efficiency, for both inference and training. The core of SD is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.01163","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/2101.01163/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":"2026-07-05T03:43:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O7H95bLq/wNkawLzFFRenQJVqtFoa7bit/m5PxhlX8WIJmMcWAXoSWvpqr0zEd2XX5yzo0SE9aLnq+6/jsqGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:43:28.693122Z"},"content_sha256":"b813f13f51d47d7e3a7f5c437186e9d2a82ef1a17f0b97c26867b6850eba72eb","schema_version":"1.0","event_id":"sha256:b813f13f51d47d7e3a7f5c437186e9d2a82ef1a17f0b97c26867b6850eba72eb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2VBPMM46COKJ3R7LZ47J4ICO32/bundle.json","state_url":"https://pith.science/pith/2VBPMM46COKJ3R7LZ47J4ICO32/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2VBPMM46COKJ3R7LZ47J4ICO32/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":"2026-07-07T10:43:28Z","links":{"resolver":"https://pith.science/pith/2VBPMM46COKJ3R7LZ47J4ICO32","bundle":"https://pith.science/pith/2VBPMM46COKJ3R7LZ47J4ICO32/bundle.json","state":"https://pith.science/pith/2VBPMM46COKJ3R7LZ47J4ICO32/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2VBPMM46COKJ3R7LZ47J4ICO32/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:2VBPMM46COKJ3R7LZ47J4ICO32","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":"6024104fb866d83903b8fcc8039cfd97eb4afb22a8face1d7c65301c46317361","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-04T18:54:07Z","title_canon_sha256":"acd66d26e97ac440ce4905dea9fa817b68033f2c12b651018d2871ef794bbb6b"},"schema_version":"1.0","source":{"id":"2101.01163","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.01163","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"arxiv_version","alias_value":"2101.01163v2","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.01163","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_12","alias_value":"2VBPMM46COKJ","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_16","alias_value":"2VBPMM46COKJ3R7L","created_at":"2026-07-05T03:43:00Z"},{"alias_kind":"pith_short_8","alias_value":"2VBPMM46","created_at":"2026-07-05T03:43:00Z"}],"graph_snapshots":[{"event_id":"sha256:b813f13f51d47d7e3a7f5c437186e9d2a82ef1a17f0b97c26867b6850eba72eb","target":"graph","created_at":"2026-07-05T03:43:00Z","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/2101.01163/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The record-breaking performance of deep neural networks (DNNs) comes with heavy parameterization, leading to external dynamic random-access memory (DRAM) for storage. The prohibitive energy of DRAM accesses makes it non-trivial to deploy DNN on resource-constrained devices, calling for minimizing the weight and data movements to improve the energy efficiency. We present SmartDeal (SD), an algorithm framework to trade higher-cost memory storage/access for lower-cost computation, in order to aggressively boost the storage and energy efficiency, for both inference and training. The core of SD is ","authors_text":"Chaojian Li, Haoran You, Pengfei Xu, Xiaohan Chen, Yang Zhao, Yingyan Lin, Yonggan Fu, Yue Wang, Zhangyang Wang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-04T18:54:07Z","title":"SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.01163","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":"sha256:00948d39633381444da92cb7de36e6334d90e204675b91d47c8fd83a064853a5","target":"record","created_at":"2026-07-05T03:43:00Z","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":"6024104fb866d83903b8fcc8039cfd97eb4afb22a8face1d7c65301c46317361","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-04T18:54:07Z","title_canon_sha256":"acd66d26e97ac440ce4905dea9fa817b68033f2c12b651018d2871ef794bbb6b"},"schema_version":"1.0","source":{"id":"2101.01163","kind":"arxiv","version":2}},"canonical_sha256":"d542f6339e13949dc7ebcf3e9e204edebcf4ef2ac29ea0a55de910ac900d4927","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d542f6339e13949dc7ebcf3e9e204edebcf4ef2ac29ea0a55de910ac900d4927","first_computed_at":"2026-07-05T03:43:00.950032Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:43:00.950032Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ku2YmkJbRYYvqGf31cvQ1L6pGWqrPRNXUpQRy4IE8WNExfd+04/D0oC3zWKzIucFs6a4NQQu3ILXYFFBEym6Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T03:43:00.950534Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.01163","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:00948d39633381444da92cb7de36e6334d90e204675b91d47c8fd83a064853a5","sha256:b813f13f51d47d7e3a7f5c437186e9d2a82ef1a17f0b97c26867b6850eba72eb"],"state_sha256":"86dcffcf649dfb03ad2cea7b64cbb2fad789d78d7d1f3f7d7cd0c1669ce2d840"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VYpc/9gyxvrdUyQ8Wvm+4X3a1suoM4nMZfdau2wtHGkOD16dGt7CsW9ekWwD7fqiNp2m7JPvxtoMIVlrrOuUDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T10:43:28.695069Z","bundle_sha256":"f22416833f458581531a5adb6f11741e0f1f0c3fa41c7f0057daea16afdd8da8"}}