{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ZBWA776AAAIQ7L7ARTBVBCRZJG","short_pith_number":"pith:ZBWA776A","canonical_record":{"source":{"id":"2212.00785","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-01T18:59:03Z","cross_cats_sorted":[],"title_canon_sha256":"6d5eef570a4ff54ca631ff2a26e2278f10b20668757f713bc9acd4b11a6af42c","abstract_canon_sha256":"755239e1f3db743bd28c59e1f91aec431e67f7b0bd63c5dd1970192b5fd919f2"},"schema_version":"1.0"},"canonical_sha256":"c86c0fffc000110fafe08cc3508a3949a7fe84334c8be1e6d18dd1bc266e3311","source":{"kind":"arxiv","id":"2212.00785","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.00785","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"arxiv_version","alias_value":"2212.00785v2","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.00785","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_12","alias_value":"ZBWA776AAAIQ","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_16","alias_value":"ZBWA776AAAIQ7L7A","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_8","alias_value":"ZBWA776A","created_at":"2026-07-05T05:54:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ZBWA776AAAIQ7L7ARTBVBCRZJG","target":"record","payload":{"canonical_record":{"source":{"id":"2212.00785","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-01T18:59:03Z","cross_cats_sorted":[],"title_canon_sha256":"6d5eef570a4ff54ca631ff2a26e2278f10b20668757f713bc9acd4b11a6af42c","abstract_canon_sha256":"755239e1f3db743bd28c59e1f91aec431e67f7b0bd63c5dd1970192b5fd919f2"},"schema_version":"1.0"},"canonical_sha256":"c86c0fffc000110fafe08cc3508a3949a7fe84334c8be1e6d18dd1bc266e3311","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:54:34.013477Z","signature_b64":"nEZ5EJa7hoNEPbQrwYQg4cvofTF4WCXNFQn+e8wl5J2Q3yrSNtvBRQc27UIIKNdlZHAVCGyYPwdR5DyjlS0YCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c86c0fffc000110fafe08cc3508a3949a7fe84334c8be1e6d18dd1bc266e3311","last_reissued_at":"2026-07-05T05:54:34.012980Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:54:34.012980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.00785","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":"2026-07-05T05:54:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fXDE4tFtIewlvXkpsDsx4kiG556A/TtFJq9E/LP6Kt0rOq1Ep8VksOzLHHfdkKW26qRqrrTIyi0U6GQrkmE5AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:22:42.459444Z"},"content_sha256":"ca15463e071c4adec7d1e71e6deccd7c4532e3a45d18aa41155cd69218edc075","schema_version":"1.0","event_id":"sha256:ca15463e071c4adec7d1e71e6deccd7c4532e3a45d18aa41155cd69218edc075"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ZBWA776AAAIQ7L7ARTBVBCRZJG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Byungseok Roh, Jonghwan Mun, Junbum Cha","submitted_at":"2022-12-01T18:59:03Z","abstract_excerpt":"We tackle open-world semantic segmentation, which aims at learning to segment arbitrary visual concepts in images, by using only image-text pairs without dense annotations. Existing open-world segmentation methods have shown impressive advances by employing contrastive learning (CL) to learn diverse visual concepts and transferring the learned image-level understanding to the segmentation task. However, these CL-based methods suffer from a train-test discrepancy, since it only considers image-text alignment during training, whereas segmentation requires region-text alignment during testing. In"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.00785","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/2212.00785/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":"2026-07-05T05:54:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"afxgC5ljN2ydwZbMv6kObO38PyJYp7Lw4frVHtCuCAR3ztX2K4/WKhOCTCOH/S31H3zsY1us3nh0vNGqiNICCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:22:42.459835Z"},"content_sha256":"27a1f7d8ecea5d120ec400cc77a13d51ceb6859a9bb43e305fc8aef71df12361","schema_version":"1.0","event_id":"sha256:27a1f7d8ecea5d120ec400cc77a13d51ceb6859a9bb43e305fc8aef71df12361"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/bundle.json","state_url":"https://pith.science/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/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":"2026-07-06T17:22:42Z","links":{"resolver":"https://pith.science/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG","bundle":"https://pith.science/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/bundle.json","state":"https://pith.science/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZBWA776AAAIQ7L7ARTBVBCRZJG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ZBWA776AAAIQ7L7ARTBVBCRZJG","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":"755239e1f3db743bd28c59e1f91aec431e67f7b0bd63c5dd1970192b5fd919f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-01T18:59:03Z","title_canon_sha256":"6d5eef570a4ff54ca631ff2a26e2278f10b20668757f713bc9acd4b11a6af42c"},"schema_version":"1.0","source":{"id":"2212.00785","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.00785","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"arxiv_version","alias_value":"2212.00785v2","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.00785","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_12","alias_value":"ZBWA776AAAIQ","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_16","alias_value":"ZBWA776AAAIQ7L7A","created_at":"2026-07-05T05:54:34Z"},{"alias_kind":"pith_short_8","alias_value":"ZBWA776A","created_at":"2026-07-05T05:54:34Z"}],"graph_snapshots":[{"event_id":"sha256:27a1f7d8ecea5d120ec400cc77a13d51ceb6859a9bb43e305fc8aef71df12361","target":"graph","created_at":"2026-07-05T05:54:34Z","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/2212.00785/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We tackle open-world semantic segmentation, which aims at learning to segment arbitrary visual concepts in images, by using only image-text pairs without dense annotations. Existing open-world segmentation methods have shown impressive advances by employing contrastive learning (CL) to learn diverse visual concepts and transferring the learned image-level understanding to the segmentation task. However, these CL-based methods suffer from a train-test discrepancy, since it only considers image-text alignment during training, whereas segmentation requires region-text alignment during testing. In","authors_text":"Byungseok Roh, Jonghwan Mun, Junbum Cha","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-01T18:59:03Z","title":"Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.00785","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:ca15463e071c4adec7d1e71e6deccd7c4532e3a45d18aa41155cd69218edc075","target":"record","created_at":"2026-07-05T05:54:34Z","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":"755239e1f3db743bd28c59e1f91aec431e67f7b0bd63c5dd1970192b5fd919f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-01T18:59:03Z","title_canon_sha256":"6d5eef570a4ff54ca631ff2a26e2278f10b20668757f713bc9acd4b11a6af42c"},"schema_version":"1.0","source":{"id":"2212.00785","kind":"arxiv","version":2}},"canonical_sha256":"c86c0fffc000110fafe08cc3508a3949a7fe84334c8be1e6d18dd1bc266e3311","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c86c0fffc000110fafe08cc3508a3949a7fe84334c8be1e6d18dd1bc266e3311","first_computed_at":"2026-07-05T05:54:34.012980Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:54:34.012980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nEZ5EJa7hoNEPbQrwYQg4cvofTF4WCXNFQn+e8wl5J2Q3yrSNtvBRQc27UIIKNdlZHAVCGyYPwdR5DyjlS0YCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:54:34.013477Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.00785","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca15463e071c4adec7d1e71e6deccd7c4532e3a45d18aa41155cd69218edc075","sha256:27a1f7d8ecea5d120ec400cc77a13d51ceb6859a9bb43e305fc8aef71df12361"],"state_sha256":"20c3d3e6eacaf84a6e404a3602dd29030c7c07097f9108ef33e9a5b934625477"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T7fEHO83aL3zFbpUBgHgzd019z7CaIZM1sfEegL32GbPrU2rWihS4gNkAd8/wuLoOI2YFrfotXFlOoeM/ov6Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:22:42.463257Z","bundle_sha256":"448799b468e1c8a9ec8f26c6b8a2b45f280467184d4b6f69162fedf5e2b49f06"}}