{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:EBC2K224RPDPZ2ICZ3CGNWF4RU","short_pith_number":"pith:EBC2K224","canonical_record":{"source":{"id":"2508.01153","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-02T02:28:09Z","cross_cats_sorted":[],"title_canon_sha256":"fdf1118e583552152d6b163af8ad2f044924663766a51296a5987d4e59e7896f","abstract_canon_sha256":"1a00c48b0c76ef67b6fd9c287e381b4e11f6207c6deaca1e0bba048236c5298c"},"schema_version":"1.0"},"canonical_sha256":"2045a56b5c8bc6fce902cec466d8bc8d06a6ccc5bdfc2f0a194b7c75f2a8aee0","source":{"kind":"arxiv","id":"2508.01153","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01153","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01153v1","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01153","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_12","alias_value":"EBC2K224RPDP","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_16","alias_value":"EBC2K224RPDPZ2IC","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_8","alias_value":"EBC2K224","created_at":"2026-07-05T11:47:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:EBC2K224RPDPZ2ICZ3CGNWF4RU","target":"record","payload":{"canonical_record":{"source":{"id":"2508.01153","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-02T02:28:09Z","cross_cats_sorted":[],"title_canon_sha256":"fdf1118e583552152d6b163af8ad2f044924663766a51296a5987d4e59e7896f","abstract_canon_sha256":"1a00c48b0c76ef67b6fd9c287e381b4e11f6207c6deaca1e0bba048236c5298c"},"schema_version":"1.0"},"canonical_sha256":"2045a56b5c8bc6fce902cec466d8bc8d06a6ccc5bdfc2f0a194b7c75f2a8aee0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:47:33.986854Z","signature_b64":"Wl+71oqEJPq6IT87iH3CHzFcv2K8c9tnxzqRsSo/krRTD2l7go4wGrg/6hSZCunl9S3bgChE8w5SGIggyNgYDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2045a56b5c8bc6fce902cec466d8bc8d06a6ccc5bdfc2f0a194b7c75f2a8aee0","last_reissued_at":"2026-07-05T11:47:33.986403Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:47:33.986403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.01153","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":"2026-07-05T11:47:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s9q3WpqrOb9rccmvLFy4sY3lW83CkH5nITOb1AhmsS9cggH9+sK+T33QpH9tMg0ZG5WQc83xoX1Sy1At8ZH2BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:01:35.153690Z"},"content_sha256":"d16ff9249804c9a522678ff18eb453516d224ee8d608729cce6fd67e583aa5e7","schema_version":"1.0","event_id":"sha256:d16ff9249804c9a522678ff18eb453516d224ee8d608729cce6fd67e583aa5e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:EBC2K224RPDPZ2ICZ3CGNWF4RU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TEACH: Text Encoding as Curriculum Hints for Scene Text Recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hui Zheng, Xiahan Yang","submitted_at":"2025-08-02T02:28:09Z","abstract_excerpt":"Scene Text Recognition (STR) remains a challenging task due to complex visual appearances and limited semantic priors. We propose TEACH, a novel training paradigm that injects ground-truth text into the model as auxiliary input and progressively reduces its influence during training. By encoding target labels into the embedding space and applying loss-aware masking, TEACH simulates a curriculum learning process that guides the model from label-dependent learning to fully visual recognition. Unlike language model-based approaches, TEACH requires no external pretraining and introduces no inferen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01153","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/2508.01153/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":"2026-07-05T11:47:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pNBZeS8KxWlc9GGQYCgMjfvEMBp4haZbBrshFV+fnknj+Gd+gpFtFn4xzyA85TNXidWVkB7/TeaFqHG0EIAvBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:01:35.154584Z"},"content_sha256":"9a415d907c5035c433be52cbfa88ea1aad887c6cfec5df4fb7a396ad9699476c","schema_version":"1.0","event_id":"sha256:9a415d907c5035c433be52cbfa88ea1aad887c6cfec5df4fb7a396ad9699476c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/bundle.json","state_url":"https://pith.science/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/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":"2026-08-07T21:01:35Z","links":{"resolver":"https://pith.science/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU","bundle":"https://pith.science/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/bundle.json","state":"https://pith.science/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EBC2K224RPDPZ2ICZ3CGNWF4RU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EBC2K224RPDPZ2ICZ3CGNWF4RU","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":"1a00c48b0c76ef67b6fd9c287e381b4e11f6207c6deaca1e0bba048236c5298c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-02T02:28:09Z","title_canon_sha256":"fdf1118e583552152d6b163af8ad2f044924663766a51296a5987d4e59e7896f"},"schema_version":"1.0","source":{"id":"2508.01153","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01153","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01153v1","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01153","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_12","alias_value":"EBC2K224RPDP","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_16","alias_value":"EBC2K224RPDPZ2IC","created_at":"2026-07-05T11:47:33Z"},{"alias_kind":"pith_short_8","alias_value":"EBC2K224","created_at":"2026-07-05T11:47:33Z"}],"graph_snapshots":[{"event_id":"sha256:9a415d907c5035c433be52cbfa88ea1aad887c6cfec5df4fb7a396ad9699476c","target":"graph","created_at":"2026-07-05T11:47:33Z","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/2508.01153/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scene Text Recognition (STR) remains a challenging task due to complex visual appearances and limited semantic priors. We propose TEACH, a novel training paradigm that injects ground-truth text into the model as auxiliary input and progressively reduces its influence during training. By encoding target labels into the embedding space and applying loss-aware masking, TEACH simulates a curriculum learning process that guides the model from label-dependent learning to fully visual recognition. Unlike language model-based approaches, TEACH requires no external pretraining and introduces no inferen","authors_text":"Hui Zheng, Xiahan Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-02T02:28:09Z","title":"TEACH: Text Encoding as Curriculum Hints for Scene Text Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01153","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:d16ff9249804c9a522678ff18eb453516d224ee8d608729cce6fd67e583aa5e7","target":"record","created_at":"2026-07-05T11:47:33Z","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":"1a00c48b0c76ef67b6fd9c287e381b4e11f6207c6deaca1e0bba048236c5298c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-02T02:28:09Z","title_canon_sha256":"fdf1118e583552152d6b163af8ad2f044924663766a51296a5987d4e59e7896f"},"schema_version":"1.0","source":{"id":"2508.01153","kind":"arxiv","version":1}},"canonical_sha256":"2045a56b5c8bc6fce902cec466d8bc8d06a6ccc5bdfc2f0a194b7c75f2a8aee0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2045a56b5c8bc6fce902cec466d8bc8d06a6ccc5bdfc2f0a194b7c75f2a8aee0","first_computed_at":"2026-07-05T11:47:33.986403Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:47:33.986403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wl+71oqEJPq6IT87iH3CHzFcv2K8c9tnxzqRsSo/krRTD2l7go4wGrg/6hSZCunl9S3bgChE8w5SGIggyNgYDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:47:33.986854Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.01153","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d16ff9249804c9a522678ff18eb453516d224ee8d608729cce6fd67e583aa5e7","sha256:9a415d907c5035c433be52cbfa88ea1aad887c6cfec5df4fb7a396ad9699476c"],"state_sha256":"19ae5396962dcb72607a2dba041a4266da12a45dc655126ccbe9f4330ea64928"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4fvfGAtiIKPB4RnEr6lrqdbo0VoXi2qNvj4JYuQIZbMg7M0FGOyr+pn+frd1oIdDme/65XtsVhKlPZOiYMTYAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T21:01:35.162210Z","bundle_sha256":"4ba5412a6c7b51c2b2d7332fdb32e79a37b59b7590a896200f926ef66e5b2c38"}}