{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BI3CC33TPYZRPAKFFQZQK2B6MA","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":"652bd53041fa3a1ced27467947f69750051d00c212b127f63a7f16a30d20f7a1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T15:34:37Z","title_canon_sha256":"5ed35e2da6d39d76d3902029e7a5fb2de9167608619bd42c6bcf222c0c4450ab"},"schema_version":"1.0","source":{"id":"2601.09566","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.09566","created_at":"2026-06-02T01:03:41Z"},{"alias_kind":"arxiv_version","alias_value":"2601.09566v4","created_at":"2026-06-02T01:03:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.09566","created_at":"2026-06-02T01:03:41Z"},{"alias_kind":"pith_short_12","alias_value":"BI3CC33TPYZR","created_at":"2026-06-02T01:03:41Z"},{"alias_kind":"pith_short_16","alias_value":"BI3CC33TPYZRPAKF","created_at":"2026-06-02T01:03:41Z"},{"alias_kind":"pith_short_8","alias_value":"BI3CC33T","created_at":"2026-06-02T01:03:41Z"}],"graph_snapshots":[{"event_id":"sha256:2381d865ecc9896b188a2bf075daeaa984ebdf01055ce895c1f777da911512e4","target":"graph","created_at":"2026-06-02T01:03:41Z","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/2601.09566/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we study whether rendering Chinese characters as visual glyph images, rather than discrete token IDs as mainstream LLMs do, providing an inductive bias for character-level language modeling. Our central finding gives a double-edged insight: visual inputs produce a pronounced hot-start effect, more than doubling early-stage accuracy within the first epoch (at 0.4% of total training steps) (12.3% visual inputs vs. 5.8% index-based baseline), yet both approaches converge to essentially identical final accuracy (39%). This pattern holds across resolutions as low as 8x8 pixels, partia","authors_text":"Hao Guan, Shuyang Xiang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T15:34:37Z","title":"Hot-Start Chinese Language Modeling:Visual Glyphs Accelerate Sample-Efficient Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.09566","kind":"arxiv","version":4},"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:e50d3be444dbfddd42e1c5042abc40395d27c4e3835ef0985d16eda6f03ff3c8","target":"record","created_at":"2026-06-02T01:03:41Z","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":"652bd53041fa3a1ced27467947f69750051d00c212b127f63a7f16a30d20f7a1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-14T15:34:37Z","title_canon_sha256":"5ed35e2da6d39d76d3902029e7a5fb2de9167608619bd42c6bcf222c0c4450ab"},"schema_version":"1.0","source":{"id":"2601.09566","kind":"arxiv","version":4}},"canonical_sha256":"0a36216f737e331781452c3305683e60228fbc19bf3b1612599efbec845ea1ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0a36216f737e331781452c3305683e60228fbc19bf3b1612599efbec845ea1ac","first_computed_at":"2026-06-02T01:03:41.002627Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T01:03:41.002627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"stTrMg3Cn6wG9AzklrUr2tijElUANjV45nJczYAOsWJg7zHzBICCAQxUOCJUWBIdtMUDfduc2GPRob0wVAr/DA==","signature_status":"signed_v1","signed_at":"2026-06-02T01:03:41.003191Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.09566","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e50d3be444dbfddd42e1c5042abc40395d27c4e3835ef0985d16eda6f03ff3c8","sha256:2381d865ecc9896b188a2bf075daeaa984ebdf01055ce895c1f777da911512e4"],"state_sha256":"9f43fbf81094de28c1a8784cc11bd5f2e02ff99035eec3d1f9433075e6da21b0"}