{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JYY5WVNFWVEADDJVC74NKDKUJR","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":"08861f5c1351741fd870639cf53cd2274df4e5f006c2602c02b4954a893f8012","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-04T14:28:42Z","title_canon_sha256":"a866981be529d3e6012d3d439cc7580fecc49e1fb553ebbb8a3669e2e463d0d7"},"schema_version":"1.0","source":{"id":"2608.03733","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.03733","created_at":"2026-08-05T01:36:58Z"},{"alias_kind":"arxiv_version","alias_value":"2608.03733v1","created_at":"2026-08-05T01:36:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.03733","created_at":"2026-08-05T01:36:58Z"},{"alias_kind":"pith_short_12","alias_value":"JYY5WVNFWVEA","created_at":"2026-08-05T01:36:58Z"},{"alias_kind":"pith_short_16","alias_value":"JYY5WVNFWVEADDJV","created_at":"2026-08-05T01:36:58Z"},{"alias_kind":"pith_short_8","alias_value":"JYY5WVNF","created_at":"2026-08-05T01:36:58Z"}],"graph_snapshots":[{"event_id":"sha256:af36ac49bf65046b0a5ae655b275a037f1aa0ac889a3c98ec4a2d6e3d5d986f4","target":"graph","created_at":"2026-08-05T01:36:58Z","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/2608.03733/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-scale, high-quality multimodal data that are costly to annotate. Self-augmentation offers a promising alternative by enabling models to expand their own training data without external supervision. However, existing MLLM self-augmentation methods are largely text-centric, while image augmentation remains underexplored and typically relies on generic or handcrafted transformations that are weakly aligned with the model's actual incapability. We p","authors_text":"Chi-Min Chan, Chunyang Jiang, Mengyang Wu, Pingping Zhang, Senkang Hu, Sitong Cheng, Wei Xue, Wenao Ma, Yike Guo, Yiyang Cai, Yuzhi Zhao, Zhijian Hou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-04T14:28:42Z","title":"Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.03733","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":"sha256:6182d6bce09a7f766e5fd20c6116e6f195e8a0c201f12b5757b7ee82f9625df1","target":"record","created_at":"2026-08-05T01:36:58Z","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":"08861f5c1351741fd870639cf53cd2274df4e5f006c2602c02b4954a893f8012","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-04T14:28:42Z","title_canon_sha256":"a866981be529d3e6012d3d439cc7580fecc49e1fb553ebbb8a3669e2e463d0d7"},"schema_version":"1.0","source":{"id":"2608.03733","kind":"arxiv","version":1}},"canonical_sha256":"4e31db55a5b548018d3517f8d50d544c769694ff6dcc58571cf27cb54696dc96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4e31db55a5b548018d3517f8d50d544c769694ff6dcc58571cf27cb54696dc96","first_computed_at":"2026-08-05T01:36:58.877345Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-05T01:36:58.877345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pSrTsvYDbEhfhUh735HC9tZeTEaTpWzADPBl8/kkfQdYgTMMfsauBZoT9jwCzyvK2hVaedyB2Tax+Vq9CV4/Aw==","signature_status":"signed_v1","signed_at":"2026-08-05T01:36:58.879114Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.03733","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6182d6bce09a7f766e5fd20c6116e6f195e8a0c201f12b5757b7ee82f9625df1","sha256:af36ac49bf65046b0a5ae655b275a037f1aa0ac889a3c98ec4a2d6e3d5d986f4"],"state_sha256":"005a57611ea0af592c066f01b67aa8e4ee1880930275ff111fb053c6361ed569"}