{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YQIX53HZKHNG3MJHKQSZYCGW3D","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":"4802bdc3460792450a24d013be102ee1f3394bd582e43556195880b5724777af","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-16T14:20:55Z","title_canon_sha256":"5389ccd86764e5619ecb3c1d0c4c44501669af2fa795c12a8ebb209bc28dc885"},"schema_version":"1.0","source":{"id":"2404.10595","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.10595","created_at":"2026-07-05T09:45:09Z"},{"alias_kind":"arxiv_version","alias_value":"2404.10595v5","created_at":"2026-07-05T09:45:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.10595","created_at":"2026-07-05T09:45:09Z"},{"alias_kind":"pith_short_12","alias_value":"YQIX53HZKHNG","created_at":"2026-07-05T09:45:09Z"},{"alias_kind":"pith_short_16","alias_value":"YQIX53HZKHNG3MJH","created_at":"2026-07-05T09:45:09Z"},{"alias_kind":"pith_short_8","alias_value":"YQIX53HZ","created_at":"2026-07-05T09:45:09Z"}],"graph_snapshots":[{"event_id":"sha256:cc368763d574a73246da39ea840d60fd21d99b274fe5f7c9f02c2d6615122d08","target":"graph","created_at":"2026-07-05T09:45:09Z","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/2404.10595/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Vision-Language Models (LVLMs) have received widespread attention for advancing the interpretable self-driving. Existing evaluations of LVLMs primarily focus on multi-faceted capabilities in natural circumstances, lacking automated and quantifiable assessment for self-driving, let alone the severe road corner cases. In this work, we propose CODA-LM, the very first benchmark for the automatic evaluation of LVLMs for self-driving corner cases. We adopt a hierarchical data structure and prompt powerful LVLMs to analyze complex driving scenes and generate high-quality pre-annotations for the","authors_text":"Dit-Yan Yeung, Huchuan Lu, Kai Chen, Lanqing Hong, Meng Tian, Pengxiang Li, Ruiyuan Gao, Wenhua Zhang, Xinhai Zhao, Xu Jia, Yanxin Liu, Yanze Li, Zhenguo Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-16T14:20:55Z","title":"Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.10595","kind":"arxiv","version":5},"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":"sha256:275a2f6ca24aa352afdaca333d214ae300ac0a8cde669036867251bf2d0342bc","target":"record","created_at":"2026-07-05T09:45:09Z","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":"4802bdc3460792450a24d013be102ee1f3394bd582e43556195880b5724777af","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-16T14:20:55Z","title_canon_sha256":"5389ccd86764e5619ecb3c1d0c4c44501669af2fa795c12a8ebb209bc28dc885"},"schema_version":"1.0","source":{"id":"2404.10595","kind":"arxiv","version":5}},"canonical_sha256":"c4117eecf951da6db12754259c08d6d8e97927bd7f00eaa4d54052e63d438ad4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c4117eecf951da6db12754259c08d6d8e97927bd7f00eaa4d54052e63d438ad4","first_computed_at":"2026-07-05T09:45:09.568276Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:45:09.568276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FO10LtkH+Lzr6/NVCm4fyW1n8jfhgR57Z4d9L+33b3uNKQylL0jh/1xZgXDjOxX3tf0LRx0GQ1Ix+VfgzKl7DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:45:09.568777Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.10595","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:275a2f6ca24aa352afdaca333d214ae300ac0a8cde669036867251bf2d0342bc","sha256:cc368763d574a73246da39ea840d60fd21d99b274fe5f7c9f02c2d6615122d08"],"state_sha256":"fc5f8837e75f2ac137517fa2fffad63091e6eb933bda207a2869e93afa2071ec"}