{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4OL6D7GABMWRJBCR2OCLIVX337","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":"a3e1d2a9cc1d25be8aa6ea8880f829cae0007687e3fd63743a4aff30a3e8f9d7","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-26T21:44:11Z","title_canon_sha256":"44879dec2d83133be88a9c21690f53cbd8c7740aedcf31fd2fc1f1551d2782c6"},"schema_version":"1.0","source":{"id":"2409.18313","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.18313","created_at":"2026-07-05T10:02:52Z"},{"alias_kind":"arxiv_version","alias_value":"2409.18313v5","created_at":"2026-07-05T10:02:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.18313","created_at":"2026-07-05T10:02:52Z"},{"alias_kind":"pith_short_12","alias_value":"4OL6D7GABMWR","created_at":"2026-07-05T10:02:52Z"},{"alias_kind":"pith_short_16","alias_value":"4OL6D7GABMWRJBCR","created_at":"2026-07-05T10:02:52Z"},{"alias_kind":"pith_short_8","alias_value":"4OL6D7GA","created_at":"2026-07-05T10:02:52Z"}],"graph_snapshots":[{"event_id":"sha256:ffa5a6ec6298b5185d083dbf3c5a6dd22fc2607759a6b6b93d4bf98c2990719f","target":"graph","created_at":"2026-07-05T10:02:52Z","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/2409.18313/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There is no limit to how much a robot might explore and learn, but all of that knowledge needs to be searchable and actionable. Within language research, retrieval augmented generation (RAG) has become the workhorse of large-scale non-parametric knowledge; however, existing techniques do not directly transfer to the embodied domain, which is multimodal, where data is highly correlated, and perception requires abstraction. To address these challenges, we introduce Embodied-RAG, a framework that enhances the foundational model of an embodied agent with a non-parametric memory system capable of a","authors_text":"Aarav Bajaj, Kedi Xu, Matthew Johnson-Roberson, Pengliang Ji, Quanting Xie, Ruslan Salakhutdinov, So Yeon Min, Tianyi Zhang, Yonatan Bisk, Yue Yang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-26T21:44:11Z","title":"Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.18313","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":"sha256:4274ed659b431cdb57a2b0f7e67c261c75115423eb0da40c510cfd83c8ac7a46","target":"record","created_at":"2026-07-05T10:02:52Z","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":"a3e1d2a9cc1d25be8aa6ea8880f829cae0007687e3fd63743a4aff30a3e8f9d7","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-26T21:44:11Z","title_canon_sha256":"44879dec2d83133be88a9c21690f53cbd8c7740aedcf31fd2fc1f1551d2782c6"},"schema_version":"1.0","source":{"id":"2409.18313","kind":"arxiv","version":5}},"canonical_sha256":"e397e1fcc00b2d148451d384b456fbdfd96968e80242e5e4e71679cbfbac64a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e397e1fcc00b2d148451d384b456fbdfd96968e80242e5e4e71679cbfbac64a0","first_computed_at":"2026-07-05T10:02:52.562561Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:02:52.562561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0xFiCvS8ZQEZEez8aUoWX2sppalUibe6A1wpfvnnOKKwa1j5dkBlsaA5OwL9MGjnzQlDXd9Y3UgqCUxfUalTAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:02:52.563125Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.18313","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4274ed659b431cdb57a2b0f7e67c261c75115423eb0da40c510cfd83c8ac7a46","sha256:ffa5a6ec6298b5185d083dbf3c5a6dd22fc2607759a6b6b93d4bf98c2990719f"],"state_sha256":"20f1e33ab416bcf934c6700b48fb9bd43d211a939c0e0053a9828efef75ebfce"}