{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:OAVBBILVQ5TTUFMYP2JPOV5XR2","short_pith_number":"pith:OAVBBILV","canonical_record":{"source":{"id":"2605.20299","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T12:34:16Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"a962f16a3f973c7867b15fa3efcbedb5e9ef342022ebf188b1918353fd538cad","abstract_canon_sha256":"9715e16a47d9828efbe3b969bf89a1063e16353689c42e067fb4fad1c1860a00"},"schema_version":"1.0"},"canonical_sha256":"702a10a17587673a15987e92f757b78eb63f0ab4a6c330fc0a896d57cbd374f9","source":{"kind":"arxiv","id":"2605.20299","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20299","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20299v1","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20299","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_12","alias_value":"OAVBBILVQ5TT","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_16","alias_value":"OAVBBILVQ5TTUFMY","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_8","alias_value":"OAVBBILV","created_at":"2026-05-21T00:04:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:OAVBBILVQ5TTUFMYP2JPOV5XR2","target":"record","payload":{"canonical_record":{"source":{"id":"2605.20299","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T12:34:16Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"a962f16a3f973c7867b15fa3efcbedb5e9ef342022ebf188b1918353fd538cad","abstract_canon_sha256":"9715e16a47d9828efbe3b969bf89a1063e16353689c42e067fb4fad1c1860a00"},"schema_version":"1.0"},"canonical_sha256":"702a10a17587673a15987e92f757b78eb63f0ab4a6c330fc0a896d57cbd374f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T00:04:24.450186Z","signature_b64":"FEWBLG7qYLVwbXBxiAaI5mo3B41gbMWhVZKzElPBVOBaQK7tsfhXmG8M9B+1Y3+egyeG9yLS0dkrNf9LauaTDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"702a10a17587673a15987e92f757b78eb63f0ab4a6c330fc0a896d57cbd374f9","last_reissued_at":"2026-05-21T00:04:24.449731Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T00:04:24.449731Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.20299","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-21T00:04:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1dfX9wQ50ceiJtSfwkv/IKAuXUPZ5xV/6PW0GN3i2leJmbVq0aVDLFpkYrs3jiVccizzHSv9vZfaQvVABmx2Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T05:05:20.254943Z"},"content_sha256":"9be4a02b5030f92e8147342029bc792947fa9d92d03d1fac76af1ed3ee1f4b39","schema_version":"1.0","event_id":"sha256:9be4a02b5030f92e8147342029bc792947fa9d92d03d1fac76af1ed3ee1f4b39"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:OAVBBILVQ5TTUFMYP2JPOV5XR2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mechanisms of Misgeneralization in Physical Sequence Modeling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.LG","authors_text":"Core Francisco Park, Hidenori Tanaka, Karun Kumar, Kento Nishi, Raphael Tang","submitted_at":"2026-05-19T12:34:16Z","abstract_excerpt":"Generative sequence models are often trained to plan motion in physical domains, from robotics to mechanical simulations. When constructing a dataset to train such a model, engineers may curate demonstrations to specify how trajectories should be distributed over a physical quantity like travel distance or mechanical energy. For example, a roboticist building a maze navigation agent might choose demonstrations whose travel distances cover a fixed range uniformly, hoping to constrain the agent's expected power usage. We find that standard deep learning can violate this intent: each generated tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20299","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.20299/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-21T00:04:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VDHcJrehFWveF/FE4EY0rdyDL9rSV5cgrIbHnTCbTvXsnAXKE+q3OViEPEuZsFmSWF93qhf4rBbaE3MUeSQlAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T05:05:20.255752Z"},"content_sha256":"d24d6107cd1391ed3712d5eed32cd4b6f53869bdd3cac78adbb8a913a50e8769","schema_version":"1.0","event_id":"sha256:d24d6107cd1391ed3712d5eed32cd4b6f53869bdd3cac78adbb8a913a50e8769"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/bundle.json","state_url":"https://pith.science/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-23T05:05:20Z","links":{"resolver":"https://pith.science/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2","bundle":"https://pith.science/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/bundle.json","state":"https://pith.science/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OAVBBILVQ5TTUFMYP2JPOV5XR2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:OAVBBILVQ5TTUFMYP2JPOV5XR2","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":"9715e16a47d9828efbe3b969bf89a1063e16353689c42e067fb4fad1c1860a00","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T12:34:16Z","title_canon_sha256":"a962f16a3f973c7867b15fa3efcbedb5e9ef342022ebf188b1918353fd538cad"},"schema_version":"1.0","source":{"id":"2605.20299","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20299","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20299v1","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20299","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_12","alias_value":"OAVBBILVQ5TT","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_16","alias_value":"OAVBBILVQ5TTUFMY","created_at":"2026-05-21T00:04:24Z"},{"alias_kind":"pith_short_8","alias_value":"OAVBBILV","created_at":"2026-05-21T00:04:24Z"}],"graph_snapshots":[{"event_id":"sha256:d24d6107cd1391ed3712d5eed32cd4b6f53869bdd3cac78adbb8a913a50e8769","target":"graph","created_at":"2026-05-21T00:04:24Z","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/2605.20299/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative sequence models are often trained to plan motion in physical domains, from robotics to mechanical simulations. When constructing a dataset to train such a model, engineers may curate demonstrations to specify how trajectories should be distributed over a physical quantity like travel distance or mechanical energy. For example, a roboticist building a maze navigation agent might choose demonstrations whose travel distances cover a fixed range uniformly, hoping to constrain the agent's expected power usage. We find that standard deep learning can violate this intent: each generated tr","authors_text":"Core Francisco Park, Hidenori Tanaka, Karun Kumar, Kento Nishi, Raphael Tang","cross_cats":["cs.AI","cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T12:34:16Z","title":"Mechanisms of Misgeneralization in Physical Sequence Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20299","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":"sha256:9be4a02b5030f92e8147342029bc792947fa9d92d03d1fac76af1ed3ee1f4b39","target":"record","created_at":"2026-05-21T00:04:24Z","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":"9715e16a47d9828efbe3b969bf89a1063e16353689c42e067fb4fad1c1860a00","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T12:34:16Z","title_canon_sha256":"a962f16a3f973c7867b15fa3efcbedb5e9ef342022ebf188b1918353fd538cad"},"schema_version":"1.0","source":{"id":"2605.20299","kind":"arxiv","version":1}},"canonical_sha256":"702a10a17587673a15987e92f757b78eb63f0ab4a6c330fc0a896d57cbd374f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"702a10a17587673a15987e92f757b78eb63f0ab4a6c330fc0a896d57cbd374f9","first_computed_at":"2026-05-21T00:04:24.449731Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T00:04:24.449731Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FEWBLG7qYLVwbXBxiAaI5mo3B41gbMWhVZKzElPBVOBaQK7tsfhXmG8M9B+1Y3+egyeG9yLS0dkrNf9LauaTDA==","signature_status":"signed_v1","signed_at":"2026-05-21T00:04:24.450186Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.20299","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9be4a02b5030f92e8147342029bc792947fa9d92d03d1fac76af1ed3ee1f4b39","sha256:d24d6107cd1391ed3712d5eed32cd4b6f53869bdd3cac78adbb8a913a50e8769"],"state_sha256":"33009cbf47be7c330475add6d9a56187a9bc85c43c6cb06d2e98a32989e5c32e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oczggDuafyE7ROYKMK6qX8KsPq+VgPOY80/fgzgHEj39+UWlVqpwPN0Bq0Y/tgLZV1bivGWTy4pHPp9sH277Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T05:05:20.259647Z","bundle_sha256":"b05aaae16fa6293e5fc90dd0d23fdefa499fb6c3960e7156800e7353392f6dca"}}