{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YB4DSTEFXFGOLYIBMUILBWOBFL","merge_version":"pith-open-graph-merge-v1","event_count":4,"valid_event_count":4,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"dbf86d5eadff5f04bf5b42ec814ecc463c96e598f8aa0881a4334cfeac45ad0a","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-12T18:47:43Z","title_canon_sha256":"8a61629e6814e8fd225658dc2653dd8da7d90df1b01d89ae0a35f3733397993c"},"schema_version":"1.0","source":{"id":"2608.12515","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.12515","created_at":"2026-08-14T00:44:16Z"},{"alias_kind":"arxiv_version","alias_value":"2608.12515v1","created_at":"2026-08-14T00:44:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.12515","created_at":"2026-08-14T00:44:16Z"},{"alias_kind":"pith_short_12","alias_value":"YB4DSTEFXFGO","created_at":"2026-08-14T00:44:16Z"},{"alias_kind":"pith_short_16","alias_value":"YB4DSTEFXFGOLYIB","created_at":"2026-08-14T00:44:16Z"},{"alias_kind":"pith_short_8","alias_value":"YB4DSTEF","created_at":"2026-08-14T00:44:16Z"}],"graph_snapshots":[{"event_id":"sha256:8127cdc9344f226899d2353c34d6aad1aac675d342edcb2205a1efbe757d43ba","target":"graph","created_at":"2026-08-14T00:44:16Z","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/2608.12515/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Assessing proxemic danger from a robot's egocentric perspective is critical for safe embodied navigation in human environments and requires both visual and contextual reasoning. We evaluate three opensource vision-language models (VLMs) (\\textit{InternVL}, \\textit{Qwen-VL}, and \\textit{SmolVLM}) on the classification of egocentric robot images into four danger levels, comparing three prompting strategies and two rounds of QLoRA fine-tuning against a stratified random baseline. Without fine-tuning, all models perform near the baseline, while fine-tuning yields only modest overall improvements. ","authors_text":"Dmytro Kuzmenko, Vladyslava Rudas","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-12T18:47:43Z","title":"Can Vision-Language Models Assess Proxemic Risk from Egocentric Robot Images?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.12515","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:e83f1707d67e400d1c6405454233740dcb85571814e930cb74b0c793c05380ba","target":"record","created_at":"2026-08-14T00:44:16Z","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":"dbf86d5eadff5f04bf5b42ec814ecc463c96e598f8aa0881a4334cfeac45ad0a","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-12T18:47:43Z","title_canon_sha256":"8a61629e6814e8fd225658dc2653dd8da7d90df1b01d89ae0a35f3733397993c"},"schema_version":"1.0","source":{"id":"2608.12515","kind":"arxiv","version":1}},"canonical_sha256":"c078394c85b94ce5e1016510b0d9c12ae961777173c69b1d9a3e724d617e6912","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c078394c85b94ce5e1016510b0d9c12ae961777173c69b1d9a3e724d617e6912","first_computed_at":"2026-08-14T00:44:16.692732Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-14T00:44:16.692732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"33omiNukJB8i5cmS0+NNFFig7e0C4sWJ3nOohEVmn8tHIH/fY6Z1k0n5+rJ1nHHcy8PY6Wq3mZO9RSeTxy5zBg==","signature_status":"signed_v1","signed_at":"2026-08-14T00:44:16.709384Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.12515","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:a07de59f1d44c7bc6342f539c5c48d74649e113108ef4894f4b713bcc10cd97a","sha256:dd1ce5ee04ddf8385103c15cd8a274a423619109a1b9653e722b47af183690fe"]}],"invalid_events":[],"applied_event_ids":["sha256:e83f1707d67e400d1c6405454233740dcb85571814e930cb74b0c793c05380ba","sha256:8127cdc9344f226899d2353c34d6aad1aac675d342edcb2205a1efbe757d43ba"],"state_sha256":"8bb9bad9df40c221b557d8e26018b7d9b6498c827c1561bb58d8f8cb40046a44"}