{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:UMHKMXSXIC2G7NK7Y5RZ2MQYAN","short_pith_number":"pith:UMHKMXSX","canonical_record":{"source":{"id":"2210.05844","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-12T00:30:26Z","cross_cats_sorted":[],"title_canon_sha256":"55239549117a66dec03dbc093e1b90ba611530e8bf19e8a875c9d45f58cd1a94","abstract_canon_sha256":"f77e9d35f4dc01375e73c08ebaeaceb6a569edb96419da618d9425e2cf24ab75"},"schema_version":"1.0"},"canonical_sha256":"a30ea65e5740b46fb55fc7639d3218035516e2fec9ca5873110bb29ff9f6b36f","source":{"kind":"arxiv","id":"2210.05844","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.05844","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"arxiv_version","alias_value":"2210.05844v2","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.05844","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_12","alias_value":"UMHKMXSXIC2G","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_16","alias_value":"UMHKMXSXIC2G7NK7","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_8","alias_value":"UMHKMXSX","created_at":"2026-07-05T05:24:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:UMHKMXSXIC2G7NK7Y5RZ2MQYAN","target":"record","payload":{"canonical_record":{"source":{"id":"2210.05844","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-12T00:30:26Z","cross_cats_sorted":[],"title_canon_sha256":"55239549117a66dec03dbc093e1b90ba611530e8bf19e8a875c9d45f58cd1a94","abstract_canon_sha256":"f77e9d35f4dc01375e73c08ebaeaceb6a569edb96419da618d9425e2cf24ab75"},"schema_version":"1.0"},"canonical_sha256":"a30ea65e5740b46fb55fc7639d3218035516e2fec9ca5873110bb29ff9f6b36f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:24:14.458238Z","signature_b64":"/6YissAO4f+M3FkxfkbWMrUiTRYkQRh7y0wHuoCMDX6jppmrajvH0WTE8mjThoe2Zhf4OyKOUMwNo/DrPfpfDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a30ea65e5740b46fb55fc7639d3218035516e2fec9ca5873110bb29ff9f6b36f","last_reissued_at":"2026-07-05T05:24:14.457819Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:24:14.457819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.05844","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:24:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GM/Uh1SiBMe0ziRkTv47wrYHxnrhDiejxXho6AuiW88EngImlZUH9gBIlI+6m1reK7SdSO4TCrtSei0gOMkwDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:29:07.083676Z"},"content_sha256":"b1cac016d4ae9ad978f37ce48006e0864384c99ee9f1256ed8c69bfdffb94e9d","schema_version":"1.0","event_id":"sha256:b1cac016d4ae9ad978f37ce48006e0864384c99ee9f1256ed8c69bfdffb94e9d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:UMHKMXSXIC2G7NK7Y5RZ2MQYAN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SegViT: Semantic Segmentation with Plain Vision Transformers","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bowen Zhang, Chunhua Shen, Quan Tang, Xiangxiang Chu, Xiaolin Wei, Yifan Liu, Zhi Tian","submitted_at":"2022-10-12T00:30:26Z","abstract_excerpt":"We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit. Previous ViT-based segmentation networks usually learn a pixel-level representation from the output of the ViT. Differently, we make use of the fundamental component -- attention mechanism, to generate masks for semantic segmentation. Specifically, we propose the Attention-to-Mask (ATM) module, in which the similarity maps between a set of learnable class tokens and the spatial feature maps are transferred to the segmentation masks. Experiments show that our proposed SegVit using the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.05844","kind":"arxiv","version":2},"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/2210.05844/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":"2026-07-05T05:24:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s7mfQdviwAvUo+2o/Lu2N++HGzPTqMU75vqfZBha3WtL1L891Fhf0iTwQnje1kR9OacfcouWqH4sXM69uc/UAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:29:07.084281Z"},"content_sha256":"3855f3ef95363b82a4a1586db36b5170d05b528e28fad04ed1dee9ac041e19ff","schema_version":"1.0","event_id":"sha256:3855f3ef95363b82a4a1586db36b5170d05b528e28fad04ed1dee9ac041e19ff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/bundle.json","state_url":"https://pith.science/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/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":"2026-08-05T02:29:07Z","links":{"resolver":"https://pith.science/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN","bundle":"https://pith.science/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/bundle.json","state":"https://pith.science/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UMHKMXSXIC2G7NK7Y5RZ2MQYAN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UMHKMXSXIC2G7NK7Y5RZ2MQYAN","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":"f77e9d35f4dc01375e73c08ebaeaceb6a569edb96419da618d9425e2cf24ab75","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-12T00:30:26Z","title_canon_sha256":"55239549117a66dec03dbc093e1b90ba611530e8bf19e8a875c9d45f58cd1a94"},"schema_version":"1.0","source":{"id":"2210.05844","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.05844","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"arxiv_version","alias_value":"2210.05844v2","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.05844","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_12","alias_value":"UMHKMXSXIC2G","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_16","alias_value":"UMHKMXSXIC2G7NK7","created_at":"2026-07-05T05:24:14Z"},{"alias_kind":"pith_short_8","alias_value":"UMHKMXSX","created_at":"2026-07-05T05:24:14Z"}],"graph_snapshots":[{"event_id":"sha256:3855f3ef95363b82a4a1586db36b5170d05b528e28fad04ed1dee9ac041e19ff","target":"graph","created_at":"2026-07-05T05:24:14Z","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/2210.05844/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit. Previous ViT-based segmentation networks usually learn a pixel-level representation from the output of the ViT. Differently, we make use of the fundamental component -- attention mechanism, to generate masks for semantic segmentation. Specifically, we propose the Attention-to-Mask (ATM) module, in which the similarity maps between a set of learnable class tokens and the spatial feature maps are transferred to the segmentation masks. Experiments show that our proposed SegVit using the","authors_text":"Bowen Zhang, Chunhua Shen, Quan Tang, Xiangxiang Chu, Xiaolin Wei, Yifan Liu, Zhi Tian","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-12T00:30:26Z","title":"SegViT: Semantic Segmentation with Plain Vision Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.05844","kind":"arxiv","version":2},"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:b1cac016d4ae9ad978f37ce48006e0864384c99ee9f1256ed8c69bfdffb94e9d","target":"record","created_at":"2026-07-05T05:24:14Z","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":"f77e9d35f4dc01375e73c08ebaeaceb6a569edb96419da618d9425e2cf24ab75","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-12T00:30:26Z","title_canon_sha256":"55239549117a66dec03dbc093e1b90ba611530e8bf19e8a875c9d45f58cd1a94"},"schema_version":"1.0","source":{"id":"2210.05844","kind":"arxiv","version":2}},"canonical_sha256":"a30ea65e5740b46fb55fc7639d3218035516e2fec9ca5873110bb29ff9f6b36f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a30ea65e5740b46fb55fc7639d3218035516e2fec9ca5873110bb29ff9f6b36f","first_computed_at":"2026-07-05T05:24:14.457819Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:24:14.457819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/6YissAO4f+M3FkxfkbWMrUiTRYkQRh7y0wHuoCMDX6jppmrajvH0WTE8mjThoe2Zhf4OyKOUMwNo/DrPfpfDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:24:14.458238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.05844","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b1cac016d4ae9ad978f37ce48006e0864384c99ee9f1256ed8c69bfdffb94e9d","sha256:3855f3ef95363b82a4a1586db36b5170d05b528e28fad04ed1dee9ac041e19ff"],"state_sha256":"9638f5bd6f19ef09fa44281ef9546fe847c14a6abeae5551721b984b8998ca92"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3zzAn2Z8Zp2My5OTilfQR/UOft37+3DJMtUkBfoq6sZo42yunMLgSniKC7vqB0MWYu+Yu8pS87Jib3VtGgaCDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:29:07.096134Z","bundle_sha256":"997240765c137b528a97c3ec24d0a59521405660c18ef0cc86e211e6ef19d91f"}}