{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:GLMPO6AFJSCQIKJXM6MFZZL25T","short_pith_number":"pith:GLMPO6AF","schema_version":"1.0","canonical_sha256":"32d8f778054c8504293767985ce57aece7444b986663306bfd434f50c5ed6b4c","source":{"kind":"arxiv","id":"2605.17907","version":1},"attestation_state":"computed","paper":{"title":"One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Congzhang Shao, Guiyang Luo, Jinglin Li, Quan Yuan, Weize Li, Xiaoyuan Fu, Xinyuan Ding, Xuanhan Zhu, Yang Li, Yunqi Ba","submitted_at":"2026-05-18T06:14:30Z","abstract_excerpt":"By sharing intermediate features, collaborative perception extends each agent's sensing beyond standalone limits, but real-world feature modality heterogeneity remains a key barrier to effective fusion. Most existing methods, including direct adaption and protocol-based transformation, typically rely on training adapters for newly emerging feature modalities and often require additional retraining or fine-tuning. Such repeated training is costly and is often infeasible across manufacturers due to model and data privacy constraints, limiting real-world scalability. To address this issue, we pro"},"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":"2605.17907","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-18T06:14:30Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"edc872cc59877bcd0bef6e5d84543e48a01f0c4229716e28b495a3163dc077a9","abstract_canon_sha256":"0ed5e0a176aeb58fba2d3680d87016c1185f2de73c663af467ca0e9a1dab7a26"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:05.210789Z","signature_b64":"l1Y0xQ1ZHn/b1wXXXhRgGchnb9NCmBA7k709xSglcnDlXF3hzPIbM3lpf49wWhmme2xvanXjz8v/HARyHVBdCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32d8f778054c8504293767985ce57aece7444b986663306bfd434f50c5ed6b4c","last_reissued_at":"2026-05-20T00:05:05.210109Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:05.210109Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Congzhang Shao, Guiyang Luo, Jinglin Li, Quan Yuan, Weize Li, Xiaoyuan Fu, Xinyuan Ding, Xuanhan Zhu, Yang Li, Yunqi Ba","submitted_at":"2026-05-18T06:14:30Z","abstract_excerpt":"By sharing intermediate features, collaborative perception extends each agent's sensing beyond standalone limits, but real-world feature modality heterogeneity remains a key barrier to effective fusion. Most existing methods, including direct adaption and protocol-based transformation, typically rely on training adapters for newly emerging feature modalities and often require additional retraining or fine-tuning. Such repeated training is costly and is often infeasible across manufacturers due to model and data privacy constraints, limiting real-world scalability. To address this issue, we pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17907","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/2605.17907/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":"2605.17907","created_at":"2026-05-20T00:05:05.210250+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.17907v1","created_at":"2026-05-20T00:05:05.210250+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17907","created_at":"2026-05-20T00:05:05.210250+00:00"},{"alias_kind":"pith_short_12","alias_value":"GLMPO6AFJSCQ","created_at":"2026-05-20T00:05:05.210250+00:00"},{"alias_kind":"pith_short_16","alias_value":"GLMPO6AFJSCQIKJX","created_at":"2026-05-20T00:05:05.210250+00:00"},{"alias_kind":"pith_short_8","alias_value":"GLMPO6AF","created_at":"2026-05-20T00:05:05.210250+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/GLMPO6AFJSCQIKJXM6MFZZL25T","json":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T.json","graph_json":"https://pith.science/api/pith-number/GLMPO6AFJSCQIKJXM6MFZZL25T/graph.json","events_json":"https://pith.science/api/pith-number/GLMPO6AFJSCQIKJXM6MFZZL25T/events.json","paper":"https://pith.science/paper/GLMPO6AF"},"agent_actions":{"view_html":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T","download_json":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T.json","view_paper":"https://pith.science/paper/GLMPO6AF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.17907&json=true","fetch_graph":"https://pith.science/api/pith-number/GLMPO6AFJSCQIKJXM6MFZZL25T/graph.json","fetch_events":"https://pith.science/api/pith-number/GLMPO6AFJSCQIKJXM6MFZZL25T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T/action/storage_attestation","attest_author":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T/action/author_attestation","sign_citation":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T/action/citation_signature","submit_replication":"https://pith.science/pith/GLMPO6AFJSCQIKJXM6MFZZL25T/action/replication_record"}},"created_at":"2026-05-20T00:05:05.210250+00:00","updated_at":"2026-05-20T00:05:05.210250+00:00"}