{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QVM56BKUITLL6KHPMWP2GAWANZ","short_pith_number":"pith:QVM56BKU","canonical_record":{"source":{"id":"2507.01016","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-01T17:59:44Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b49b2f5162e514afd61e97db36cb78f2d10797c86f8a0b7b14144a79b7ca5a05","abstract_canon_sha256":"9b2368b18b767b43f6f85b76fffe092b5ce2d4e6a02b61bdf9acd3c172541768"},"schema_version":"1.0"},"canonical_sha256":"8559df055444d6bf28ef659fa302c06e42f1f0171c16f931c3789cc379bc3dfe","source":{"kind":"arxiv","id":"2507.01016","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.01016","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"arxiv_version","alias_value":"2507.01016v1","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01016","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_12","alias_value":"QVM56BKUITLL","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"QVM56BKUITLL6KHP","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"QVM56BKU","created_at":"2026-07-05T11:30:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QVM56BKUITLL6KHPMWP2GAWANZ","target":"record","payload":{"canonical_record":{"source":{"id":"2507.01016","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-01T17:59:44Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b49b2f5162e514afd61e97db36cb78f2d10797c86f8a0b7b14144a79b7ca5a05","abstract_canon_sha256":"9b2368b18b767b43f6f85b76fffe092b5ce2d4e6a02b61bdf9acd3c172541768"},"schema_version":"1.0"},"canonical_sha256":"8559df055444d6bf28ef659fa302c06e42f1f0171c16f931c3789cc379bc3dfe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:30:19.618993Z","signature_b64":"X4QClZHPA+q2myyv1TLJivKxVpy/xvIJY6gCGW4MruLYHDcpANsSEPBkEm//vVHk7w8IyqSBVSaLkI6KvqQKCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8559df055444d6bf28ef659fa302c06e42f1f0171c16f931c3789cc379bc3dfe","last_reissued_at":"2026-07-05T11:30:19.618547Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:30:19.618547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.01016","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":"2026-07-05T11:30:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bcjUu+DgACxfLhZ4dvCDpUZczqgAl25Le9mEeyF83wK3O14NpvLgeU9Yyom3Ii2YRwJrC4zGuezAeP0vEQWoAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:02:30.680819Z"},"content_sha256":"e71c63d1fc24abbe99458d8b28ca8a796f06bb7160405cd22b2bfd67246f8763","schema_version":"1.0","event_id":"sha256:e71c63d1fc24abbe99458d8b28ca8a796f06bb7160405cd22b2bfd67246f8763"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QVM56BKUITLL6KHPMWP2GAWANZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Hao-Shu Fang, Haoyi Zhu, Jiange Yang, Mingyu Liu, Tong He, Yating Wang","submitted_at":"2025-07-01T17:59:44Z","abstract_excerpt":"In this paper, we introduce an innovative vector quantization based action tokenizer built upon the largest-scale action trajectory dataset to date, leveraging over 100 times more data than previous approaches. This extensive dataset enables our tokenizer to capture rich spatiotemporal dynamics, resulting in a model that not only accelerates inference but also generates smoother and more coherent action outputs. Once trained, the tokenizer can be seamlessly adapted to a wide range of downstream tasks in a zero-shot manner, from short-horizon reactive behaviors to long-horizon planning. A key f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01016","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/2507.01016/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":"2026-07-05T11:30:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"igPI1NeaWqUhDHxFLa/9lIk+OwubjLTywM0AoR12tIiEahvtX7R3omf+lUiG6k6MpkuBIAlf6w/RwKAuPUs0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:02:30.681761Z"},"content_sha256":"b5729712210dc1af6ff173382e97c45428e751f23a45ae8b547563e1f725d6f7","schema_version":"1.0","event_id":"sha256:b5729712210dc1af6ff173382e97c45428e751f23a45ae8b547563e1f725d6f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QVM56BKUITLL6KHPMWP2GAWANZ/bundle.json","state_url":"https://pith.science/pith/QVM56BKUITLL6KHPMWP2GAWANZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QVM56BKUITLL6KHPMWP2GAWANZ/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":"2026-08-04T17:02:30Z","links":{"resolver":"https://pith.science/pith/QVM56BKUITLL6KHPMWP2GAWANZ","bundle":"https://pith.science/pith/QVM56BKUITLL6KHPMWP2GAWANZ/bundle.json","state":"https://pith.science/pith/QVM56BKUITLL6KHPMWP2GAWANZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QVM56BKUITLL6KHPMWP2GAWANZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QVM56BKUITLL6KHPMWP2GAWANZ","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":"9b2368b18b767b43f6f85b76fffe092b5ce2d4e6a02b61bdf9acd3c172541768","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-01T17:59:44Z","title_canon_sha256":"b49b2f5162e514afd61e97db36cb78f2d10797c86f8a0b7b14144a79b7ca5a05"},"schema_version":"1.0","source":{"id":"2507.01016","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.01016","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"arxiv_version","alias_value":"2507.01016v1","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01016","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_12","alias_value":"QVM56BKUITLL","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"QVM56BKUITLL6KHP","created_at":"2026-07-05T11:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"QVM56BKU","created_at":"2026-07-05T11:30:19Z"}],"graph_snapshots":[{"event_id":"sha256:b5729712210dc1af6ff173382e97c45428e751f23a45ae8b547563e1f725d6f7","target":"graph","created_at":"2026-07-05T11:30:19Z","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/2507.01016/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce an innovative vector quantization based action tokenizer built upon the largest-scale action trajectory dataset to date, leveraging over 100 times more data than previous approaches. This extensive dataset enables our tokenizer to capture rich spatiotemporal dynamics, resulting in a model that not only accelerates inference but also generates smoother and more coherent action outputs. Once trained, the tokenizer can be seamlessly adapted to a wide range of downstream tasks in a zero-shot manner, from short-horizon reactive behaviors to long-horizon planning. A key f","authors_text":"Hao-Shu Fang, Haoyi Zhu, Jiange Yang, Mingyu Liu, Tong He, Yating Wang","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-01T17:59:44Z","title":"VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01016","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:e71c63d1fc24abbe99458d8b28ca8a796f06bb7160405cd22b2bfd67246f8763","target":"record","created_at":"2026-07-05T11:30:19Z","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":"9b2368b18b767b43f6f85b76fffe092b5ce2d4e6a02b61bdf9acd3c172541768","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-01T17:59:44Z","title_canon_sha256":"b49b2f5162e514afd61e97db36cb78f2d10797c86f8a0b7b14144a79b7ca5a05"},"schema_version":"1.0","source":{"id":"2507.01016","kind":"arxiv","version":1}},"canonical_sha256":"8559df055444d6bf28ef659fa302c06e42f1f0171c16f931c3789cc379bc3dfe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8559df055444d6bf28ef659fa302c06e42f1f0171c16f931c3789cc379bc3dfe","first_computed_at":"2026-07-05T11:30:19.618547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:30:19.618547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X4QClZHPA+q2myyv1TLJivKxVpy/xvIJY6gCGW4MruLYHDcpANsSEPBkEm//vVHk7w8IyqSBVSaLkI6KvqQKCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:30:19.618993Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.01016","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e71c63d1fc24abbe99458d8b28ca8a796f06bb7160405cd22b2bfd67246f8763","sha256:b5729712210dc1af6ff173382e97c45428e751f23a45ae8b547563e1f725d6f7"],"state_sha256":"39e2aba61f703c93100336519a95f3ddaef2bb6be5592783cad81c1b1fb52004"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hFM4ib8uHCzkdXErpcrHGmAjawrAawkO6VbibUOlR16jGxuaIZY5NK+0F3SwjgueBGDQRwhc/D6kT/xNq0qxDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T17:02:30.689262Z","bundle_sha256":"84bbaa1b40d874cf2f0f913e924c7e18ec82b8ca1b62c384523b1e4767f47b78"}}