{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WQJJ7UWBGA66CQGEKVEDP2UZSK","short_pith_number":"pith:WQJJ7UWB","canonical_record":{"source":{"id":"2606.06832","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-05T02:16:50Z","cross_cats_sorted":[],"title_canon_sha256":"e8d9c5298d86c4c04aa4ddc28cf923d5a478b03dc7c07edeec0a5b05b4cb8a0e","abstract_canon_sha256":"6b32a9dff22d5fce5f2db74bd54f3791b2ceba8535443d8fe9552cbc329b9e08"},"schema_version":"1.0"},"canonical_sha256":"b4129fd2c1303de140c4554837ea999298da89062bfcb5c249aa97addfdbfc96","source":{"kind":"arxiv","id":"2606.06832","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.06832","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"arxiv_version","alias_value":"2606.06832v1","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06832","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_12","alias_value":"WQJJ7UWBGA66","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_16","alias_value":"WQJJ7UWBGA66CQGE","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_8","alias_value":"WQJJ7UWB","created_at":"2026-06-08T01:04:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WQJJ7UWBGA66CQGEKVEDP2UZSK","target":"record","payload":{"canonical_record":{"source":{"id":"2606.06832","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-05T02:16:50Z","cross_cats_sorted":[],"title_canon_sha256":"e8d9c5298d86c4c04aa4ddc28cf923d5a478b03dc7c07edeec0a5b05b4cb8a0e","abstract_canon_sha256":"6b32a9dff22d5fce5f2db74bd54f3791b2ceba8535443d8fe9552cbc329b9e08"},"schema_version":"1.0"},"canonical_sha256":"b4129fd2c1303de140c4554837ea999298da89062bfcb5c249aa97addfdbfc96","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-08T01:04:30.719710Z","signature_b64":"M/OAOmfu1LC29wP75Rqw1lxywW4gxYEyYm7TN7K/30CdGNuwqiaTMGERpI8mCTQkC3w2EwbLPYSLVDdZOf3JCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4129fd2c1303de140c4554837ea999298da89062bfcb5c249aa97addfdbfc96","last_reissued_at":"2026-06-08T01:04:30.718986Z","signature_status":"signed_v1","first_computed_at":"2026-06-08T01:04:30.718986Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.06832","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":"2026-06-08T01:04:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RVFTnmEBWEMtCJCuc2k9zdthu/3+46eh0nNAIPR3aEAOH6QeCydYWIyrtsvP/NWg0yOJ37mYkD+wJNXuktYaBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T13:09:47.320772Z"},"content_sha256":"49dd27bb1d8415947fd24f7d9ce89415ad181d0d7c872cb3c9105bbadcb66e86","schema_version":"1.0","event_id":"sha256:49dd27bb1d8415947fd24f7d9ce89415ad181d0d7c872cb3c9105bbadcb66e86"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WQJJ7UWBGA66CQGEKVEDP2UZSK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Abhiroop Ajith, Constantinos Chamzas","submitted_at":"2026-06-05T02:16:50Z","abstract_excerpt":"Robots performing long-horizon visual manipulation observe high-dimensional images, but successful plans depend on action-relevant facts: what can be done now and what changes afterward. A useful planning representation should discard irrelevant visual details while preserving action applicability and effects. Classical task planners exploit this structure through symbolic operators with preconditions and effects, but obtaining such representations from raw visual experience remains challenging. We study a visual task-planning setting in which a robot receives only image transitions: the curre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06832","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/2606.06832/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":"2026-06-08T01:04:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vN0I6E6mRRU4IgRbe4rOnovt9NVAjHFzX3iYX3/9OT9jOX1b15CZQPF2pF6UV5uvxBFy0BMA0NYk9pAQfSqcCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T13:09:47.321975Z"},"content_sha256":"a5462195b4a6c79305137a8f69d7d5b5a503913862ae59dc9a90aa9e98f08284","schema_version":"1.0","event_id":"sha256:a5462195b4a6c79305137a8f69d7d5b5a503913862ae59dc9a90aa9e98f08284"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/bundle.json","state_url":"https://pith.science/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/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":"2026-06-10T13:09:47Z","links":{"resolver":"https://pith.science/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK","bundle":"https://pith.science/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/bundle.json","state":"https://pith.science/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WQJJ7UWBGA66CQGEKVEDP2UZSK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WQJJ7UWBGA66CQGEKVEDP2UZSK","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":"6b32a9dff22d5fce5f2db74bd54f3791b2ceba8535443d8fe9552cbc329b9e08","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-05T02:16:50Z","title_canon_sha256":"e8d9c5298d86c4c04aa4ddc28cf923d5a478b03dc7c07edeec0a5b05b4cb8a0e"},"schema_version":"1.0","source":{"id":"2606.06832","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.06832","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"arxiv_version","alias_value":"2606.06832v1","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06832","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_12","alias_value":"WQJJ7UWBGA66","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_16","alias_value":"WQJJ7UWBGA66CQGE","created_at":"2026-06-08T01:04:30Z"},{"alias_kind":"pith_short_8","alias_value":"WQJJ7UWB","created_at":"2026-06-08T01:04:30Z"}],"graph_snapshots":[{"event_id":"sha256:a5462195b4a6c79305137a8f69d7d5b5a503913862ae59dc9a90aa9e98f08284","target":"graph","created_at":"2026-06-08T01:04:30Z","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/2606.06832/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robots performing long-horizon visual manipulation observe high-dimensional images, but successful plans depend on action-relevant facts: what can be done now and what changes afterward. A useful planning representation should discard irrelevant visual details while preserving action applicability and effects. Classical task planners exploit this structure through symbolic operators with preconditions and effects, but obtaining such representations from raw visual experience remains challenging. We study a visual task-planning setting in which a robot receives only image transitions: the curre","authors_text":"Abhiroop Ajith, Constantinos Chamzas","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-05T02:16:50Z","title":"STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06832","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":"sha256:49dd27bb1d8415947fd24f7d9ce89415ad181d0d7c872cb3c9105bbadcb66e86","target":"record","created_at":"2026-06-08T01:04:30Z","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":"6b32a9dff22d5fce5f2db74bd54f3791b2ceba8535443d8fe9552cbc329b9e08","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-05T02:16:50Z","title_canon_sha256":"e8d9c5298d86c4c04aa4ddc28cf923d5a478b03dc7c07edeec0a5b05b4cb8a0e"},"schema_version":"1.0","source":{"id":"2606.06832","kind":"arxiv","version":1}},"canonical_sha256":"b4129fd2c1303de140c4554837ea999298da89062bfcb5c249aa97addfdbfc96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b4129fd2c1303de140c4554837ea999298da89062bfcb5c249aa97addfdbfc96","first_computed_at":"2026-06-08T01:04:30.718986Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-08T01:04:30.718986Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M/OAOmfu1LC29wP75Rqw1lxywW4gxYEyYm7TN7K/30CdGNuwqiaTMGERpI8mCTQkC3w2EwbLPYSLVDdZOf3JCQ==","signature_status":"signed_v1","signed_at":"2026-06-08T01:04:30.719710Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.06832","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:49dd27bb1d8415947fd24f7d9ce89415ad181d0d7c872cb3c9105bbadcb66e86","sha256:a5462195b4a6c79305137a8f69d7d5b5a503913862ae59dc9a90aa9e98f08284"],"state_sha256":"2a5002d631e7ac8a10966ced405840713e6310044074bf5d73116c911a97024b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7sUNy8ElqZ8CA1Y3vEPwSunQPkEZwyqK5CIdMt1RxLt8ZW85ct6glOqTL2FkBmFgUXOJMMJDy77LqyWIj8I5AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T13:09:47.326494Z","bundle_sha256":"d2b4dfe9e2d8d69e6c2bb1ada0dacbadc3090f59c42c8f726fce9f2a42c253e5"}}