{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XAYWHEAW4ODDZZEPI6QZNHPAGD","short_pith_number":"pith:XAYWHEAW","schema_version":"1.0","canonical_sha256":"b831639016e3863ce48f47a1969de030c0e09dde58ac5a420898dd316fdc4df5","source":{"kind":"arxiv","id":"2607.01088","version":1},"attestation_state":"computed","paper":{"title":"ROSA: A Robotics Foundation Model Serving System for Robot Factories","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.RO","authors_text":"Alperen Degirmenci, Christos Kozyrakis, Hugo Hadfield, Jason Clemons, Rowland O'Flaherty, Shuran Song, Wenqi Jiang, Yashraj Narang","submitted_at":"2026-07-01T15:45:08Z","abstract_excerpt":"Robotics foundation models (RFMs) are making general-purpose robots increasingly practical for factory deployments. While RFM serving systems are central to this vision, existing systems are largely shaped by a single-robot, single-model assumption: inference is treated as an edge-computing problem handled by an on-robot or dedicated nearby GPU, and the serving objective is to minimize the latency of a single action model. In this paper, we propose ROSA, an RFM serving system for robot factories designed around three key principles. First, ROSA adopts shared GPU-pool serving, allowing a fleet "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.01088","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-07-01T15:45:08Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"bdfae556e8d01d24a77f58670e29cf8752ba24df0056ec21976726bf1d3b6758","abstract_canon_sha256":"81956fe6d41298e029d726ca617b3bc1517325cc3c3b671e7f6b2fbee9dade20"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T01:18:28.393926Z","signature_b64":"OFQziUYDlGE6muAQAUh4IiqYHbH2ki/DohH4WvxxMK/O0dZOgMWO3HUwKcrCDq06bEZ5WVTHI56DL8IBTHVlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b831639016e3863ce48f47a1969de030c0e09dde58ac5a420898dd316fdc4df5","last_reissued_at":"2026-07-02T01:18:28.393421Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T01:18:28.393421Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ROSA: A Robotics Foundation Model Serving System for Robot Factories","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.RO","authors_text":"Alperen Degirmenci, Christos Kozyrakis, Hugo Hadfield, Jason Clemons, Rowland O'Flaherty, Shuran Song, Wenqi Jiang, Yashraj Narang","submitted_at":"2026-07-01T15:45:08Z","abstract_excerpt":"Robotics foundation models (RFMs) are making general-purpose robots increasingly practical for factory deployments. While RFM serving systems are central to this vision, existing systems are largely shaped by a single-robot, single-model assumption: inference is treated as an edge-computing problem handled by an on-robot or dedicated nearby GPU, and the serving objective is to minimize the latency of a single action model. In this paper, we propose ROSA, an RFM serving system for robot factories designed around three key principles. First, ROSA adopts shared GPU-pool serving, allowing a fleet "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.01088","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/2607.01088/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.01088","created_at":"2026-07-02T01:18:28.393488+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.01088v1","created_at":"2026-07-02T01:18:28.393488+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.01088","created_at":"2026-07-02T01:18:28.393488+00:00"},{"alias_kind":"pith_short_12","alias_value":"XAYWHEAW4ODD","created_at":"2026-07-02T01:18:28.393488+00:00"},{"alias_kind":"pith_short_16","alias_value":"XAYWHEAW4ODDZZEP","created_at":"2026-07-02T01:18:28.393488+00:00"},{"alias_kind":"pith_short_8","alias_value":"XAYWHEAW","created_at":"2026-07-02T01:18:28.393488+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD","json":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD.json","graph_json":"https://pith.science/api/pith-number/XAYWHEAW4ODDZZEPI6QZNHPAGD/graph.json","events_json":"https://pith.science/api/pith-number/XAYWHEAW4ODDZZEPI6QZNHPAGD/events.json","paper":"https://pith.science/paper/XAYWHEAW"},"agent_actions":{"view_html":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD","download_json":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD.json","view_paper":"https://pith.science/paper/XAYWHEAW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.01088&json=true","fetch_graph":"https://pith.science/api/pith-number/XAYWHEAW4ODDZZEPI6QZNHPAGD/graph.json","fetch_events":"https://pith.science/api/pith-number/XAYWHEAW4ODDZZEPI6QZNHPAGD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD/action/storage_attestation","attest_author":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD/action/author_attestation","sign_citation":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD/action/citation_signature","submit_replication":"https://pith.science/pith/XAYWHEAW4ODDZZEPI6QZNHPAGD/action/replication_record"}},"created_at":"2026-07-02T01:18:28.393488+00:00","updated_at":"2026-07-02T01:18:28.393488+00:00"}