{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NNEKIH2HZJNCAWTQFIBDRRKCFM","short_pith_number":"pith:NNEKIH2H","canonical_record":{"source":{"id":"2606.20867","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T18:54:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"86c329db39492a4f554e8dcea99fca562351184a52d43e42191b53e17db47a50","abstract_canon_sha256":"f4cba47c7e2143ebc9bb6ea369b3b0c8e24e0dab14f8db64cc47b65a6cd16fd5"},"schema_version":"1.0"},"canonical_sha256":"6b48a41f47ca5a205a702a0238c5422b19bbb8410dceb9e99c68ec1122c38726","source":{"kind":"arxiv","id":"2606.20867","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20867","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20867v1","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20867","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_12","alias_value":"NNEKIH2HZJNC","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_16","alias_value":"NNEKIH2HZJNCAWTQ","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_8","alias_value":"NNEKIH2H","created_at":"2026-06-23T00:12:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NNEKIH2HZJNCAWTQFIBDRRKCFM","target":"record","payload":{"canonical_record":{"source":{"id":"2606.20867","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T18:54:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"86c329db39492a4f554e8dcea99fca562351184a52d43e42191b53e17db47a50","abstract_canon_sha256":"f4cba47c7e2143ebc9bb6ea369b3b0c8e24e0dab14f8db64cc47b65a6cd16fd5"},"schema_version":"1.0"},"canonical_sha256":"6b48a41f47ca5a205a702a0238c5422b19bbb8410dceb9e99c68ec1122c38726","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T00:12:01.306174Z","signature_b64":"mvytmHhF4h2lE9U6NxIh4Q85EDn9w7s2dhIg8ZduLoBM0pBixTl6J2xXGy+1Ur9C1/jhCRozHzq7CYZI7oDHCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6b48a41f47ca5a205a702a0238c5422b19bbb8410dceb9e99c68ec1122c38726","last_reissued_at":"2026-06-23T00:12:01.305745Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T00:12:01.305745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.20867","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":"2026-06-23T00:12:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BlCPWUhUdaft3QU7NXeEkaff30sy1ibUOml/tXLHH0ExBHO85BBSdxCWiBQXjQx6zrZW+9BFbRRXCSKcHaZuCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T00:49:59.494114Z"},"content_sha256":"f06ca5c6262b19964dd9d55178b2272ac5c80c70dc408e559d450d81896de8b3","schema_version":"1.0","event_id":"sha256:f06ca5c6262b19964dd9d55178b2272ac5c80c70dc408e559d450d81896de8b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NNEKIH2HZJNCAWTQFIBDRRKCFM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"An Thai Le, Artur Habuda, Bao Thach, Binh Gia Nguyen, Daniel Sonntag, Doanh Le, Duc Minh Nguyen, Duy M. H. Nguyen, Hung Ngo, Khoa D. Doan, Matthias Niepert, Minh N. Vu, Nghiem Tuong Diep, Ngo Anh Vien, Nhat X. Tran, Nhiem Tran, Philip Lund M{\\o}ller, Tan Q. Nguyen, Thien-Loc Ha, Tran Nguyen Le, Trong-Bao Ho, Tuan A. Tran, Vu Duong","submitted_at":"2026-06-18T18:54:51Z","abstract_excerpt":"Vision-Language-Action (VLA) models enable general-purpose robotic control via large-scale multimodal pretraining, yet their effectiveness under few-shot imitation learning remains limited. We conduct a systematic stress test of state-of-the-art VLA models and show that performance degrades sharply as demonstrations are reduced, revealing a key weakness of existing adaptation strategies. To address this, we introduce FOCA, a future-oriented conditioning framework for data-efficient VLA adaptation. FOCA combines explicit prediction of task-grounded future interaction embeddings with implicit al"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20867","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/2606.20867/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":"2026-06-23T00:12:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pSftDnnycWOCoWJ4kFa5xAhCtXgmwTSWxKUBaxQ2jfhPSH0Dzf3amLg2zrCaiktLsYuoeZaZl56XSe8N0rfyDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T00:49:59.494510Z"},"content_sha256":"2fd2940cdd78c018496685083e3bd950ea06bc862a340b9719c60028bc8ca172","schema_version":"1.0","event_id":"sha256:2fd2940cdd78c018496685083e3bd950ea06bc862a340b9719c60028bc8ca172"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/bundle.json","state_url":"https://pith.science/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/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":"2026-06-27T00:49:59Z","links":{"resolver":"https://pith.science/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM","bundle":"https://pith.science/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/bundle.json","state":"https://pith.science/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NNEKIH2HZJNCAWTQFIBDRRKCFM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NNEKIH2HZJNCAWTQFIBDRRKCFM","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":"f4cba47c7e2143ebc9bb6ea369b3b0c8e24e0dab14f8db64cc47b65a6cd16fd5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T18:54:51Z","title_canon_sha256":"86c329db39492a4f554e8dcea99fca562351184a52d43e42191b53e17db47a50"},"schema_version":"1.0","source":{"id":"2606.20867","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20867","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20867v1","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20867","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_12","alias_value":"NNEKIH2HZJNC","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_16","alias_value":"NNEKIH2HZJNCAWTQ","created_at":"2026-06-23T00:12:01Z"},{"alias_kind":"pith_short_8","alias_value":"NNEKIH2H","created_at":"2026-06-23T00:12:01Z"}],"graph_snapshots":[{"event_id":"sha256:2fd2940cdd78c018496685083e3bd950ea06bc862a340b9719c60028bc8ca172","target":"graph","created_at":"2026-06-23T00:12:01Z","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/2606.20867/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-Language-Action (VLA) models enable general-purpose robotic control via large-scale multimodal pretraining, yet their effectiveness under few-shot imitation learning remains limited. We conduct a systematic stress test of state-of-the-art VLA models and show that performance degrades sharply as demonstrations are reduced, revealing a key weakness of existing adaptation strategies. To address this, we introduce FOCA, a future-oriented conditioning framework for data-efficient VLA adaptation. FOCA combines explicit prediction of task-grounded future interaction embeddings with implicit al","authors_text":"An Thai Le, Artur Habuda, Bao Thach, Binh Gia Nguyen, Daniel Sonntag, Doanh Le, Duc Minh Nguyen, Duy M. H. Nguyen, Hung Ngo, Khoa D. Doan, Matthias Niepert, Minh N. Vu, Nghiem Tuong Diep, Ngo Anh Vien, Nhat X. Tran, Nhiem Tran, Philip Lund M{\\o}ller, Tan Q. Nguyen, Thien-Loc Ha, Tran Nguyen Le, Trong-Bao Ho, Tuan A. Tran, Vu Duong","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T18:54:51Z","title":"FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20867","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:f06ca5c6262b19964dd9d55178b2272ac5c80c70dc408e559d450d81896de8b3","target":"record","created_at":"2026-06-23T00:12:01Z","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":"f4cba47c7e2143ebc9bb6ea369b3b0c8e24e0dab14f8db64cc47b65a6cd16fd5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T18:54:51Z","title_canon_sha256":"86c329db39492a4f554e8dcea99fca562351184a52d43e42191b53e17db47a50"},"schema_version":"1.0","source":{"id":"2606.20867","kind":"arxiv","version":1}},"canonical_sha256":"6b48a41f47ca5a205a702a0238c5422b19bbb8410dceb9e99c68ec1122c38726","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6b48a41f47ca5a205a702a0238c5422b19bbb8410dceb9e99c68ec1122c38726","first_computed_at":"2026-06-23T00:12:01.305745Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T00:12:01.305745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mvytmHhF4h2lE9U6NxIh4Q85EDn9w7s2dhIg8ZduLoBM0pBixTl6J2xXGy+1Ur9C1/jhCRozHzq7CYZI7oDHCA==","signature_status":"signed_v1","signed_at":"2026-06-23T00:12:01.306174Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.20867","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f06ca5c6262b19964dd9d55178b2272ac5c80c70dc408e559d450d81896de8b3","sha256:2fd2940cdd78c018496685083e3bd950ea06bc862a340b9719c60028bc8ca172"],"state_sha256":"a4bf842c4c7f8e0073d491201f4b982f1c816fed0fd652adce3bf22941775816"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u6PyxbgtGFtLmhV1f69w8KhCrAo0BnGVZ1rwy3ZwVku/4iNdEP2r7WQyo1nECX8g62SxHt8MeqN9qusLZhM4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T00:49:59.496491Z","bundle_sha256":"f39b029f8ca80184cad57180dae615aaa0bfcb60debb70c9a1d05082b00f9ed8"}}