{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:V45QM4QC44JQG3PTWIZ6FUZIDE","short_pith_number":"pith:V45QM4QC","canonical_record":{"source":{"id":"2209.10441","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-21T15:35:02Z","cross_cats_sorted":[],"title_canon_sha256":"7ca65db159fa357a7a3f3a7098f73e839d98a5e7fd240d2ae71ff0f52d3f9af8","abstract_canon_sha256":"a1677a5d01c0ba7ec23f6715cca25aa5a3edb021bdfcf22072ee6376ddc948c9"},"schema_version":"1.0"},"canonical_sha256":"af3b067202e713036df3b233e2d32819035e295b804cc9f8d8ccc9c729477497","source":{"kind":"arxiv","id":"2209.10441","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.10441","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"arxiv_version","alias_value":"2209.10441v1","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.10441","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_12","alias_value":"V45QM4QC44JQ","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_16","alias_value":"V45QM4QC44JQG3PT","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_8","alias_value":"V45QM4QC","created_at":"2026-07-05T04:59:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:V45QM4QC44JQG3PTWIZ6FUZIDE","target":"record","payload":{"canonical_record":{"source":{"id":"2209.10441","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-21T15:35:02Z","cross_cats_sorted":[],"title_canon_sha256":"7ca65db159fa357a7a3f3a7098f73e839d98a5e7fd240d2ae71ff0f52d3f9af8","abstract_canon_sha256":"a1677a5d01c0ba7ec23f6715cca25aa5a3edb021bdfcf22072ee6376ddc948c9"},"schema_version":"1.0"},"canonical_sha256":"af3b067202e713036df3b233e2d32819035e295b804cc9f8d8ccc9c729477497","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:59:54.465709Z","signature_b64":"7zvm4RNJ71XTpPf6OVseICmA4f2GuF8wsIs0mAdF30vx0hJ3fWHe30p5Hxqlf3+DbpPCa3gIVLyBbKZTqKx4Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af3b067202e713036df3b233e2d32819035e295b804cc9f8d8ccc9c729477497","last_reissued_at":"2026-07-05T04:59:54.465257Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:59:54.465257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.10441","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":"2026-07-05T04:59:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g2EmoAILOR8zTB/v090IkIwrFWQTVAQmG4fwlCsDCmzZzuRgZxMy6xIzp2XYHddLFXVON4HZDUDP97okIhenBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T09:16:56.694766Z"},"content_sha256":"1eedcbb065c36b1bbe7efe81d766d17b7c81c87a6509e10f63a0b991b658ded6","schema_version":"1.0","event_id":"sha256:1eedcbb065c36b1bbe7efe81d766d17b7c81c87a6509e10f63a0b991b658ded6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:V45QM4QC44JQG3PTWIZ6FUZIDE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alicia Forn\\'es, Angelo Marcelli, Asma Bensalah, Giuseppe De Gregorio, Josep Llad\\'os, Mohamed Ali Souibgui, Sanket Biswas","submitted_at":"2022-09-21T15:35:02Z","abstract_excerpt":"Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhib"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.10441","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/2209.10441/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":"2026-07-05T04:59:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tczjNde8kygSvq73FSjWGEmK2c5+EIXjaXOeL8iXOrlrzH+FxxkDjl44dOLkhLJT5PQIT9SITqE75azxUFG+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T09:16:56.695130Z"},"content_sha256":"5f35572bdca9fe4ca52db5ae12d10cd486293f97d07047e0bd50147bcb7f6915","schema_version":"1.0","event_id":"sha256:5f35572bdca9fe4ca52db5ae12d10cd486293f97d07047e0bd50147bcb7f6915"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/bundle.json","state_url":"https://pith.science/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/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":"2026-07-19T09:16:56Z","links":{"resolver":"https://pith.science/pith/V45QM4QC44JQG3PTWIZ6FUZIDE","bundle":"https://pith.science/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/bundle.json","state":"https://pith.science/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V45QM4QC44JQG3PTWIZ6FUZIDE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:V45QM4QC44JQG3PTWIZ6FUZIDE","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":"a1677a5d01c0ba7ec23f6715cca25aa5a3edb021bdfcf22072ee6376ddc948c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-21T15:35:02Z","title_canon_sha256":"7ca65db159fa357a7a3f3a7098f73e839d98a5e7fd240d2ae71ff0f52d3f9af8"},"schema_version":"1.0","source":{"id":"2209.10441","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.10441","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"arxiv_version","alias_value":"2209.10441v1","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.10441","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_12","alias_value":"V45QM4QC44JQ","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_16","alias_value":"V45QM4QC44JQG3PT","created_at":"2026-07-05T04:59:54Z"},{"alias_kind":"pith_short_8","alias_value":"V45QM4QC","created_at":"2026-07-05T04:59:54Z"}],"graph_snapshots":[{"event_id":"sha256:5f35572bdca9fe4ca52db5ae12d10cd486293f97d07047e0bd50147bcb7f6915","target":"graph","created_at":"2026-07-05T04:59:54Z","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/2209.10441/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhib","authors_text":"Alicia Forn\\'es, Angelo Marcelli, Asma Bensalah, Giuseppe De Gregorio, Josep Llad\\'os, Mohamed Ali Souibgui, Sanket Biswas","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-21T15:35:02Z","title":"A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.10441","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":"sha256:1eedcbb065c36b1bbe7efe81d766d17b7c81c87a6509e10f63a0b991b658ded6","target":"record","created_at":"2026-07-05T04:59:54Z","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":"a1677a5d01c0ba7ec23f6715cca25aa5a3edb021bdfcf22072ee6376ddc948c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-21T15:35:02Z","title_canon_sha256":"7ca65db159fa357a7a3f3a7098f73e839d98a5e7fd240d2ae71ff0f52d3f9af8"},"schema_version":"1.0","source":{"id":"2209.10441","kind":"arxiv","version":1}},"canonical_sha256":"af3b067202e713036df3b233e2d32819035e295b804cc9f8d8ccc9c729477497","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af3b067202e713036df3b233e2d32819035e295b804cc9f8d8ccc9c729477497","first_computed_at":"2026-07-05T04:59:54.465257Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:59:54.465257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7zvm4RNJ71XTpPf6OVseICmA4f2GuF8wsIs0mAdF30vx0hJ3fWHe30p5Hxqlf3+DbpPCa3gIVLyBbKZTqKx4Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T04:59:54.465709Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.10441","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1eedcbb065c36b1bbe7efe81d766d17b7c81c87a6509e10f63a0b991b658ded6","sha256:5f35572bdca9fe4ca52db5ae12d10cd486293f97d07047e0bd50147bcb7f6915"],"state_sha256":"419a8eec57ea1f6c1b4e39c1ffb97b95cf660acadc085f4f7a5d95048cb2a466"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EbHwaLVmAv8b31iaOwiSZhaZ5283zD1CQb9XdbiijDjlvrRy0u85hl/5GA2HgrSXpuIJUZ3q0gWZBfm3wkL6DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T09:16:56.697256Z","bundle_sha256":"5260cb8dcb5464e7de9881a1736b2687cbf1cf74a6952d612f68ac5262669dec"}}