{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XHZADZDWWPMWYRTQ5B3THS3LNV","short_pith_number":"pith:XHZADZDW","canonical_record":{"source":{"id":"2204.07288","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-15T01:52:45Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3b34de81bfde9fd15b5a460721c72cddab0ca857bdff3f447b1eb14823e635ef","abstract_canon_sha256":"645c0fcd1e23508d9e67ef0c8103981f1bcf13a9bed74608a94eff74e94acd49"},"schema_version":"1.0"},"canonical_sha256":"b9f201e476b3d96c4670e87733cb6b6d4cf044cca387fa684384ced31ed7e1b9","source":{"kind":"arxiv","id":"2204.07288","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.07288","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2204.07288v1","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.07288","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"XHZADZDWWPMW","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"XHZADZDWWPMWYRTQ","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"XHZADZDW","created_at":"2026-07-05T04:14:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XHZADZDWWPMWYRTQ5B3THS3LNV","target":"record","payload":{"canonical_record":{"source":{"id":"2204.07288","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-15T01:52:45Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3b34de81bfde9fd15b5a460721c72cddab0ca857bdff3f447b1eb14823e635ef","abstract_canon_sha256":"645c0fcd1e23508d9e67ef0c8103981f1bcf13a9bed74608a94eff74e94acd49"},"schema_version":"1.0"},"canonical_sha256":"b9f201e476b3d96c4670e87733cb6b6d4cf044cca387fa684384ced31ed7e1b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:14:53.520295Z","signature_b64":"V8wDFJ6VrDWTfCLytpzWpru/ZSIkG1yrxCLPEbleK6YBqVGjFmdIZaunWZcGwv78Ce1x+JSonFa4APYS03XqBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9f201e476b3d96c4670e87733cb6b6d4cf044cca387fa684384ced31ed7e1b9","last_reissued_at":"2026-07-05T04:14:53.519902Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:14:53.519902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2204.07288","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":"2026-07-05T04:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sYfCQNCDtVDFey2K3ed5QKruuyvAZkPdeomQbbGMmFyOA43tTYFOzTGqMFpRdGlIqjbIuPgLFtuRcFn3jsO3Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:36:29.537783Z"},"content_sha256":"3541571f1954580a401b21b177317748811ac088e829ef12f77efa0caa92c64a","schema_version":"1.0","event_id":"sha256:3541571f1954580a401b21b177317748811ac088e829ef12f77efa0caa92c64a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XHZADZDWWPMWYRTQ5B3THS3LNV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Bhuwan Dhingra, Lisa Wu Wills, Phyllis Ang","submitted_at":"2022-04-15T01:52:45Z","abstract_excerpt":"With many real-world applications of Natural Language Processing (NLP) comprising of long texts, there has been a rise in NLP benchmarks that measure the accuracy of models that can handle longer input sequences. However, these benchmarks do not consider the trade-offs between accuracy, speed, and power consumption as input sizes or model sizes are varied. In this work, we perform a systematic study of this accuracy vs. efficiency trade-off on two widely used long-sequence models - Longformer-Encoder-Decoder (LED) and Big Bird - during fine-tuning and inference on four datasets from the SCROLL"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.07288","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/2204.07288/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":"2026-07-05T04:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hXaEp6ZWiWD8/i409NZ9Mwf9KMrVjLQVc1HlxXH+HBCiVfZdbw5t4toTAtxBQyqFdr0RAzCROUQr5/mGzug6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:36:29.539116Z"},"content_sha256":"df539d17e09970ab0a2c5e814e68c2f63296c9d1ad6a9bc6eeae8ed62b5f4d28","schema_version":"1.0","event_id":"sha256:df539d17e09970ab0a2c5e814e68c2f63296c9d1ad6a9bc6eeae8ed62b5f4d28"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/bundle.json","state_url":"https://pith.science/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/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":"2026-08-14T06:36:29Z","links":{"resolver":"https://pith.science/pith/XHZADZDWWPMWYRTQ5B3THS3LNV","bundle":"https://pith.science/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/bundle.json","state":"https://pith.science/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XHZADZDWWPMWYRTQ5B3THS3LNV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XHZADZDWWPMWYRTQ5B3THS3LNV","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":"645c0fcd1e23508d9e67ef0c8103981f1bcf13a9bed74608a94eff74e94acd49","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-15T01:52:45Z","title_canon_sha256":"3b34de81bfde9fd15b5a460721c72cddab0ca857bdff3f447b1eb14823e635ef"},"schema_version":"1.0","source":{"id":"2204.07288","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.07288","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2204.07288v1","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.07288","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"XHZADZDWWPMW","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"XHZADZDWWPMWYRTQ","created_at":"2026-07-05T04:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"XHZADZDW","created_at":"2026-07-05T04:14:53Z"}],"graph_snapshots":[{"event_id":"sha256:df539d17e09970ab0a2c5e814e68c2f63296c9d1ad6a9bc6eeae8ed62b5f4d28","target":"graph","created_at":"2026-07-05T04:14:53Z","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/2204.07288/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With many real-world applications of Natural Language Processing (NLP) comprising of long texts, there has been a rise in NLP benchmarks that measure the accuracy of models that can handle longer input sequences. However, these benchmarks do not consider the trade-offs between accuracy, speed, and power consumption as input sizes or model sizes are varied. In this work, we perform a systematic study of this accuracy vs. efficiency trade-off on two widely used long-sequence models - Longformer-Encoder-Decoder (LED) and Big Bird - during fine-tuning and inference on four datasets from the SCROLL","authors_text":"Bhuwan Dhingra, Lisa Wu Wills, Phyllis Ang","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-15T01:52:45Z","title":"Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.07288","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":"sha256:3541571f1954580a401b21b177317748811ac088e829ef12f77efa0caa92c64a","target":"record","created_at":"2026-07-05T04:14:53Z","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":"645c0fcd1e23508d9e67ef0c8103981f1bcf13a9bed74608a94eff74e94acd49","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-15T01:52:45Z","title_canon_sha256":"3b34de81bfde9fd15b5a460721c72cddab0ca857bdff3f447b1eb14823e635ef"},"schema_version":"1.0","source":{"id":"2204.07288","kind":"arxiv","version":1}},"canonical_sha256":"b9f201e476b3d96c4670e87733cb6b6d4cf044cca387fa684384ced31ed7e1b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9f201e476b3d96c4670e87733cb6b6d4cf044cca387fa684384ced31ed7e1b9","first_computed_at":"2026-07-05T04:14:53.519902Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:14:53.519902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V8wDFJ6VrDWTfCLytpzWpru/ZSIkG1yrxCLPEbleK6YBqVGjFmdIZaunWZcGwv78Ce1x+JSonFa4APYS03XqBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:14:53.520295Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.07288","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3541571f1954580a401b21b177317748811ac088e829ef12f77efa0caa92c64a","sha256:df539d17e09970ab0a2c5e814e68c2f63296c9d1ad6a9bc6eeae8ed62b5f4d28"],"state_sha256":"4598b1dfc780bbd241cd8afa6d693458a7d8c4c44737adf604e38db4588c2d3e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d91Z9MOfQ4QzgOMAKGajmUx2YE/sLsOhmsmWATp5nCJ3PnCbjKh81jVufWDBgcmkatNsMcjJQ1/cQLKBENyPDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T06:36:29.625119Z","bundle_sha256":"3fa2aabd806a47395c188d99ea18ba87f0ce9b6e5b5fd95479a8ff72a442fc21"}}