{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TVHDJ4N2EF4J37UEEKLDJSP6WG","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":"441b0faac38f5e38e79b193be1a36a4a5219c9906229e9f0ced6bac341df353d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-10-01T07:27:15Z","title_canon_sha256":"c5f9003b574ebb67b346cb0d2143b749b807c5b9c79584dfac798e1ff1db18f6"},"schema_version":"1.0","source":{"id":"2510.00600","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.00600","created_at":"2026-05-20T01:04:58Z"},{"alias_kind":"arxiv_version","alias_value":"2510.00600v2","created_at":"2026-05-20T01:04:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.00600","created_at":"2026-05-20T01:04:58Z"},{"alias_kind":"pith_short_12","alias_value":"TVHDJ4N2EF4J","created_at":"2026-05-20T01:04:58Z"},{"alias_kind":"pith_short_16","alias_value":"TVHDJ4N2EF4J37UE","created_at":"2026-05-20T01:04:58Z"},{"alias_kind":"pith_short_8","alias_value":"TVHDJ4N2","created_at":"2026-05-20T01:04:58Z"}],"graph_snapshots":[{"event_id":"sha256:9738949fc189dab6292e1e5c0de195ad4a7e283afda82d990b79fd95eeec5d6a","target":"graph","created_at":"2026-05-20T01:04:58Z","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/2510.00600/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Using Large Language Models to produce intermediate thoughts, a.k.a. Chain-of-thought (CoT), before providing an answer has been a successful recipe for solving complex language tasks. In robotics, similar embodied CoT strategies, generating thoughts before actions, have also been shown to lead to improved performance when using Vision-Language-Action models (VLAs). As these techniques increase the length of the model's generated outputs to include the thoughts, the inference time is negatively affected. Delaying an agent's actions in real-world executions, as in robotic manipulation settings,","authors_text":"Cansu Sancaktar, Daniel Dijkman, Markus Peschl, Pietro Mazzaglia","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-10-01T07:27:15Z","title":"Hybrid Training for Vision-Language-Action Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.00600","kind":"arxiv","version":2},"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:c3696ddfccf5af073df08564ceed4d3ea0d97f5cb3ca5d1e9a2ee559f3e2d803","target":"record","created_at":"2026-05-20T01:04:58Z","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":"441b0faac38f5e38e79b193be1a36a4a5219c9906229e9f0ced6bac341df353d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-10-01T07:27:15Z","title_canon_sha256":"c5f9003b574ebb67b346cb0d2143b749b807c5b9c79584dfac798e1ff1db18f6"},"schema_version":"1.0","source":{"id":"2510.00600","kind":"arxiv","version":2}},"canonical_sha256":"9d4e34f1ba21789dfe84229634c9feb19fd63f2ec1ec907a3e1d20b5fcdb742d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d4e34f1ba21789dfe84229634c9feb19fd63f2ec1ec907a3e1d20b5fcdb742d","first_computed_at":"2026-05-20T01:04:58.820638Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T01:04:58.820638Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G01ZRKvmAmbQtjneur/RfmEgKNx6LbG9TNNckFlp6YwP9YxZpSfAxDbDg3ovtRIv8Cdu4++mPJnjQd0ODMfGBw==","signature_status":"signed_v1","signed_at":"2026-05-20T01:04:58.821589Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.00600","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c3696ddfccf5af073df08564ceed4d3ea0d97f5cb3ca5d1e9a2ee559f3e2d803","sha256:9738949fc189dab6292e1e5c0de195ad4a7e283afda82d990b79fd95eeec5d6a"],"state_sha256":"8d67dffa43e9b21cc84d233bd82f5a199db56bb611a9688f6adb6f1731c2b0fe"}