{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:HYNSXEL3YQEYDYBSELQ4BBA37A","short_pith_number":"pith:HYNSXEL3","canonical_record":{"source":{"id":"2210.02617","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-06T00:33:01Z","cross_cats_sorted":[],"title_canon_sha256":"e05867d9e374dadbb41a7ca65b2472173047e2197be09c8f0bb65670aa1c3f3e","abstract_canon_sha256":"9034259ec2f5b654c986e12518c67cf7899aaff1eb57818a210ce3c28aadb2f2"},"schema_version":"1.0"},"canonical_sha256":"3e1b2b917bc40981e03222e1c0841bf82e52068cf9ed35af0c68a9f2907623ca","source":{"kind":"arxiv","id":"2210.02617","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.02617","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"arxiv_version","alias_value":"2210.02617v1","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.02617","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_12","alias_value":"HYNSXEL3YQEY","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_16","alias_value":"HYNSXEL3YQEYDYBS","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_8","alias_value":"HYNSXEL3","created_at":"2026-07-05T05:03:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:HYNSXEL3YQEYDYBSELQ4BBA37A","target":"record","payload":{"canonical_record":{"source":{"id":"2210.02617","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-06T00:33:01Z","cross_cats_sorted":[],"title_canon_sha256":"e05867d9e374dadbb41a7ca65b2472173047e2197be09c8f0bb65670aa1c3f3e","abstract_canon_sha256":"9034259ec2f5b654c986e12518c67cf7899aaff1eb57818a210ce3c28aadb2f2"},"schema_version":"1.0"},"canonical_sha256":"3e1b2b917bc40981e03222e1c0841bf82e52068cf9ed35af0c68a9f2907623ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:03:54.694698Z","signature_b64":"KXHQ6ezmd9S98HAfulxaezbVoOCUmbFszulcshKfZ/Xi2IUSPTq48NkxFz34Ark47pSoVSdcjhy9a6Kx9lRUCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e1b2b917bc40981e03222e1c0841bf82e52068cf9ed35af0c68a9f2907623ca","last_reissued_at":"2026-07-05T05:03:54.694271Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:03:54.694271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.02617","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":"2026-07-05T05:03:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5tMU6T4RfCal0bk116bCUrFjRnbI8ct0WGVBYyIM7I6Y/8uK+sOItWSu4jhsuDmAfUGeFgxrPtc0dHSD9OTBBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:36:58.712874Z"},"content_sha256":"d4b73070a0d9f4cec9b98c1d6a3d85d41d5327768eff56c9d40512ed0f7682d8","schema_version":"1.0","event_id":"sha256:d4b73070a0d9f4cec9b98c1d6a3d85d41d5327768eff56c9d40512ed0f7682d8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:HYNSXEL3YQEYDYBSELQ4BBA37A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalization Properties of Retrieval-based Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ankit Singh Rawat, Manzil Zaheer, Soumya Basu","submitted_at":"2022-10-06T00:33:01Z","abstract_excerpt":"Many modern high-performing machine learning models such as GPT-3 primarily rely on scaling up models, e.g., transformer networks. Simultaneously, a parallel line of work aims to improve the model performance by augmenting an input instance with other (labeled) instances during inference. Examples of such augmentations include task-specific prompts and similar examples retrieved from the training data by a nonparametric component. Remarkably, retrieval-based methods have enjoyed success on a wide range of problems, ranging from standard natural language processing and vision tasks to protein f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.02617","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/2210.02617/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":"2026-07-05T05:03:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xXgAh2oZXmpA4yh5/zA2XDXTBFPQ+SZAeKDqEkinj3X8EknjWtzL/T5M1aR0jOHonrQIP37lN6yhOsb1JClqAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:36:58.713503Z"},"content_sha256":"df5498faf685261e88337f93edee6eb83566a8de1ca84f320924c98eadc196a4","schema_version":"1.0","event_id":"sha256:df5498faf685261e88337f93edee6eb83566a8de1ca84f320924c98eadc196a4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/bundle.json","state_url":"https://pith.science/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/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":"2026-08-05T00:36:58Z","links":{"resolver":"https://pith.science/pith/HYNSXEL3YQEYDYBSELQ4BBA37A","bundle":"https://pith.science/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/bundle.json","state":"https://pith.science/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HYNSXEL3YQEYDYBSELQ4BBA37A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HYNSXEL3YQEYDYBSELQ4BBA37A","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":"9034259ec2f5b654c986e12518c67cf7899aaff1eb57818a210ce3c28aadb2f2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-06T00:33:01Z","title_canon_sha256":"e05867d9e374dadbb41a7ca65b2472173047e2197be09c8f0bb65670aa1c3f3e"},"schema_version":"1.0","source":{"id":"2210.02617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.02617","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"arxiv_version","alias_value":"2210.02617v1","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.02617","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_12","alias_value":"HYNSXEL3YQEY","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_16","alias_value":"HYNSXEL3YQEYDYBS","created_at":"2026-07-05T05:03:54Z"},{"alias_kind":"pith_short_8","alias_value":"HYNSXEL3","created_at":"2026-07-05T05:03:54Z"}],"graph_snapshots":[{"event_id":"sha256:df5498faf685261e88337f93edee6eb83566a8de1ca84f320924c98eadc196a4","target":"graph","created_at":"2026-07-05T05:03:54Z","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/2210.02617/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many modern high-performing machine learning models such as GPT-3 primarily rely on scaling up models, e.g., transformer networks. Simultaneously, a parallel line of work aims to improve the model performance by augmenting an input instance with other (labeled) instances during inference. Examples of such augmentations include task-specific prompts and similar examples retrieved from the training data by a nonparametric component. Remarkably, retrieval-based methods have enjoyed success on a wide range of problems, ranging from standard natural language processing and vision tasks to protein f","authors_text":"Ankit Singh Rawat, Manzil Zaheer, Soumya Basu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-06T00:33:01Z","title":"Generalization Properties of Retrieval-based Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.02617","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:d4b73070a0d9f4cec9b98c1d6a3d85d41d5327768eff56c9d40512ed0f7682d8","target":"record","created_at":"2026-07-05T05:03:54Z","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":"9034259ec2f5b654c986e12518c67cf7899aaff1eb57818a210ce3c28aadb2f2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-06T00:33:01Z","title_canon_sha256":"e05867d9e374dadbb41a7ca65b2472173047e2197be09c8f0bb65670aa1c3f3e"},"schema_version":"1.0","source":{"id":"2210.02617","kind":"arxiv","version":1}},"canonical_sha256":"3e1b2b917bc40981e03222e1c0841bf82e52068cf9ed35af0c68a9f2907623ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e1b2b917bc40981e03222e1c0841bf82e52068cf9ed35af0c68a9f2907623ca","first_computed_at":"2026-07-05T05:03:54.694271Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:03:54.694271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KXHQ6ezmd9S98HAfulxaezbVoOCUmbFszulcshKfZ/Xi2IUSPTq48NkxFz34Ark47pSoVSdcjhy9a6Kx9lRUCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:03:54.694698Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.02617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4b73070a0d9f4cec9b98c1d6a3d85d41d5327768eff56c9d40512ed0f7682d8","sha256:df5498faf685261e88337f93edee6eb83566a8de1ca84f320924c98eadc196a4"],"state_sha256":"f4694a3f0d1c78d0c08eec71f72f3fac6add65c2ae99338df9a693f2426e6c5c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZVrDvsIwqjMckVHG+gu1pS/X+rTdIsBw0PXyE218I8xUIgEY1gQ/4VNzjLyBmkm772lOrMgtKWk6ZuoKQfHfDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T00:36:58.717133Z","bundle_sha256":"0cc6fb940a5546c7db4989f5faa7c86337958975d65676c409013faf65eb384c"}}