{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:G52JPDTG3FSCJKZXOBZ6O7KGF6","short_pith_number":"pith:G52JPDTG","canonical_record":{"source":{"id":"2409.19846","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T01:13:03Z","cross_cats_sorted":[],"title_canon_sha256":"dfc5c8431c4c45bf55b5433c294efd821ec9dba08818568d9e5fff0348bdfa05","abstract_canon_sha256":"24d4d4aee2707841fe9d004ec6829db116b28c09299503a44b40e8e6923d08a8"},"schema_version":"1.0"},"canonical_sha256":"3774978e66d96424ab377073e77d462f9ca3eedb67c659f2f3dd941bb8de74b2","source":{"kind":"arxiv","id":"2409.19846","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.19846","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2409.19846v1","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.19846","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"G52JPDTG3FSC","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"G52JPDTG3FSCJKZX","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"G52JPDTG","created_at":"2026-07-05T09:13:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:G52JPDTG3FSCJKZXOBZ6O7KGF6","target":"record","payload":{"canonical_record":{"source":{"id":"2409.19846","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T01:13:03Z","cross_cats_sorted":[],"title_canon_sha256":"dfc5c8431c4c45bf55b5433c294efd821ec9dba08818568d9e5fff0348bdfa05","abstract_canon_sha256":"24d4d4aee2707841fe9d004ec6829db116b28c09299503a44b40e8e6923d08a8"},"schema_version":"1.0"},"canonical_sha256":"3774978e66d96424ab377073e77d462f9ca3eedb67c659f2f3dd941bb8de74b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:13:23.691608Z","signature_b64":"9nqtRX9qomqS3UfzNYbdGi7Iw862+yQoYcrO22WiqQKTB+eSp0FcEawjL3g0VJhsVkXZaA5tQqEccaSNK9JqBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3774978e66d96424ab377073e77d462f9ca3eedb67c659f2f3dd941bb8de74b2","last_reissued_at":"2026-07-05T09:13:23.691097Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:13:23.691097Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.19846","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":"2026-07-05T09:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i03AxV557+3yVUoByyGabtK7QgYdVjQVSkrqNyVRAEV10DXZJCBtbRW0Fgvrc0J8aeYyeRrHeOU0ea1x07c+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:00:36.919737Z"},"content_sha256":"983fa3feb9c447b683c253027239df6bf5c632db240c588f630253a222f6457a","schema_version":"1.0","event_id":"sha256:983fa3feb9c447b683c253027239df6bf5c632db240c588f630253a222f6457a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:G52JPDTG3FSCJKZXOBZ6O7KGF6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anurag Arnab, Chaehyun Kim, Heeseong Shin, Paul Hongsuck Seo, Seokju Cho, Seungryong Kim, Sunghwan Hong","submitted_at":"2024-09-30T01:13:03Z","abstract_excerpt":"Large-scale vision-language models like CLIP have demonstrated impressive open-vocabulary capabilities for image-level tasks, excelling in recognizing what objects are present. However, they struggle with pixel-level recognition tasks like semantic segmentation, which additionally require understanding where the objects are located. In this work, we propose a novel method, PixelCLIP, to adapt the CLIP image encoder for pixel-level understanding by guiding the model on where, which is achieved using unlabeled images and masks generated from vision foundation models such as SAM and DINO. To addr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.19846","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/2409.19846/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":"2026-07-05T09:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HqkijEkCIZY3UqoX2LT9jgQ32PSN8WFXK20R38RyH/0gwArpZLZN+i9S5fQgflX2CjngvO/NZ65or52Bq1pqCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:00:36.920648Z"},"content_sha256":"3a39525b495fb0d2e67b9af4eb3cc7e91b09430f7c6195b5939929de6d1a8fa2","schema_version":"1.0","event_id":"sha256:3a39525b495fb0d2e67b9af4eb3cc7e91b09430f7c6195b5939929de6d1a8fa2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/bundle.json","state_url":"https://pith.science/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/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":"2026-08-04T17:00:36Z","links":{"resolver":"https://pith.science/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6","bundle":"https://pith.science/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/bundle.json","state":"https://pith.science/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G52JPDTG3FSCJKZXOBZ6O7KGF6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:G52JPDTG3FSCJKZXOBZ6O7KGF6","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":"24d4d4aee2707841fe9d004ec6829db116b28c09299503a44b40e8e6923d08a8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T01:13:03Z","title_canon_sha256":"dfc5c8431c4c45bf55b5433c294efd821ec9dba08818568d9e5fff0348bdfa05"},"schema_version":"1.0","source":{"id":"2409.19846","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.19846","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2409.19846v1","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.19846","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"G52JPDTG3FSC","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"G52JPDTG3FSCJKZX","created_at":"2026-07-05T09:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"G52JPDTG","created_at":"2026-07-05T09:13:23Z"}],"graph_snapshots":[{"event_id":"sha256:3a39525b495fb0d2e67b9af4eb3cc7e91b09430f7c6195b5939929de6d1a8fa2","target":"graph","created_at":"2026-07-05T09:13:23Z","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/2409.19846/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale vision-language models like CLIP have demonstrated impressive open-vocabulary capabilities for image-level tasks, excelling in recognizing what objects are present. However, they struggle with pixel-level recognition tasks like semantic segmentation, which additionally require understanding where the objects are located. In this work, we propose a novel method, PixelCLIP, to adapt the CLIP image encoder for pixel-level understanding by guiding the model on where, which is achieved using unlabeled images and masks generated from vision foundation models such as SAM and DINO. To addr","authors_text":"Anurag Arnab, Chaehyun Kim, Heeseong Shin, Paul Hongsuck Seo, Seokju Cho, Seungryong Kim, Sunghwan Hong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T01:13:03Z","title":"Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.19846","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":"sha256:983fa3feb9c447b683c253027239df6bf5c632db240c588f630253a222f6457a","target":"record","created_at":"2026-07-05T09:13:23Z","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":"24d4d4aee2707841fe9d004ec6829db116b28c09299503a44b40e8e6923d08a8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T01:13:03Z","title_canon_sha256":"dfc5c8431c4c45bf55b5433c294efd821ec9dba08818568d9e5fff0348bdfa05"},"schema_version":"1.0","source":{"id":"2409.19846","kind":"arxiv","version":1}},"canonical_sha256":"3774978e66d96424ab377073e77d462f9ca3eedb67c659f2f3dd941bb8de74b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3774978e66d96424ab377073e77d462f9ca3eedb67c659f2f3dd941bb8de74b2","first_computed_at":"2026-07-05T09:13:23.691097Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:13:23.691097Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9nqtRX9qomqS3UfzNYbdGi7Iw862+yQoYcrO22WiqQKTB+eSp0FcEawjL3g0VJhsVkXZaA5tQqEccaSNK9JqBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:13:23.691608Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.19846","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:983fa3feb9c447b683c253027239df6bf5c632db240c588f630253a222f6457a","sha256:3a39525b495fb0d2e67b9af4eb3cc7e91b09430f7c6195b5939929de6d1a8fa2"],"state_sha256":"08cae868de75735a216d26a5cbeff56bc06fa278d4542921852cc2799a2aa796"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1yPpCL+MFCfQNT1tFnZ1hMwWZUNQA7ff3NA6S7B6owaj57F7QWT+8d+tOOsP2LBciNdhmVJDxcf8U5DwZpmcBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T17:00:36.926009Z","bundle_sha256":"c77ab51d1edd795e269e18b28e030f8d5d76872d0580d9b784e89541dcf351d0"}}