{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:DTXCIUIBCJQUMAAJKBQPOS6L2M","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":"2d7327b3991df9ceeb664a2ee440fa19075c0b1eead56ab617e39a87da2dd0e8","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-27T10:17:28Z","title_canon_sha256":"26809c3415abca7a8fa24bc9b490de106f201f574726d33ac6461694272394bd"},"schema_version":"1.0","source":{"id":"2009.12812","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.12812","created_at":"2026-07-05T01:41:57Z"},{"alias_kind":"arxiv_version","alias_value":"2009.12812v3","created_at":"2026-07-05T01:41:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.12812","created_at":"2026-07-05T01:41:57Z"},{"alias_kind":"pith_short_12","alias_value":"DTXCIUIBCJQU","created_at":"2026-07-05T01:41:57Z"},{"alias_kind":"pith_short_16","alias_value":"DTXCIUIBCJQUMAAJ","created_at":"2026-07-05T01:41:57Z"},{"alias_kind":"pith_short_8","alias_value":"DTXCIUIB","created_at":"2026-07-05T01:41:57Z"}],"graph_snapshots":[{"event_id":"sha256:43f46df41172bbee4e6b0ac272c26f5e75984fc02e2c48a7a98bfb5ecc113b93","target":"graph","created_at":"2026-07-05T01:41:57Z","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/2009.12812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transformer-based pre-training models like BERT have achieved remarkable performance in many natural language processing tasks.However, these models are both computation and memory expensive, hindering their deployment to resource-constrained devices. In this work, we propose TernaryBERT, which ternarizes the weights in a fine-tuned BERT model. Specifically, we use both approximation-based and loss-aware ternarization methods and empirically investigate the ternarization granularity of different parts of BERT. Moreover, to reduce the accuracy degradation caused by the lower capacity of low bit","authors_text":"Lifeng Shang, Lu Hou, Qun Liu, Wei Zhang, Xiao Chen, Xin Jiang, Yichun Yin","cross_cats":["cs.LG","cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-27T10:17:28Z","title":"TernaryBERT: Distillation-aware Ultra-low Bit BERT"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.12812","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:b8969f5e9076a6fed98c002a4d171f151986987e717b6589e0e3b28027a1cf64","target":"record","created_at":"2026-07-05T01:41:57Z","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":"2d7327b3991df9ceeb664a2ee440fa19075c0b1eead56ab617e39a87da2dd0e8","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-27T10:17:28Z","title_canon_sha256":"26809c3415abca7a8fa24bc9b490de106f201f574726d33ac6461694272394bd"},"schema_version":"1.0","source":{"id":"2009.12812","kind":"arxiv","version":3}},"canonical_sha256":"1cee24510112614600095060f74bcbd307eb053657af59a344a1f045879026eb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1cee24510112614600095060f74bcbd307eb053657af59a344a1f045879026eb","first_computed_at":"2026-07-05T01:41:57.493991Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:41:57.493991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CDIfdDcXNnUM/SFcaf1bD3ulSHXxTXi++rbzbbtdK66FM61w/SdINI7aOfKX45BFhln76DN7ROErcsFkMn3TAg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:41:57.494435Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.12812","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b8969f5e9076a6fed98c002a4d171f151986987e717b6589e0e3b28027a1cf64","sha256:43f46df41172bbee4e6b0ac272c26f5e75984fc02e2c48a7a98bfb5ecc113b93"],"state_sha256":"76d779838cba97c1d22273f588bc9f055cfb593681298973ac679f0f9398283e"}