{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:G3DVPTARHVNS27B6VRT37PUWBX","short_pith_number":"pith:G3DVPTAR","canonical_record":{"source":{"id":"2410.04842","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-07T08:59:05Z","cross_cats_sorted":[],"title_canon_sha256":"cd59b268c40ba2a7f1c95c38d07deb2a69e47c55984d9f4218457e722385a81e","abstract_canon_sha256":"d322d899e51d3c4db5607b14ea8519756c2fa5b3c906516c4a542057c52c4196"},"schema_version":"1.0"},"canonical_sha256":"36c757cc113d5b2d7c3eac67bfbe960df84ddd1cef2239e48ff2486821ff13a0","source":{"kind":"arxiv","id":"2410.04842","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04842","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04842v2","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04842","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"G3DVPTARHVNS","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"G3DVPTARHVNS27B6","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"G3DVPTAR","created_at":"2026-07-05T09:17:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:G3DVPTARHVNS27B6VRT37PUWBX","target":"record","payload":{"canonical_record":{"source":{"id":"2410.04842","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-07T08:59:05Z","cross_cats_sorted":[],"title_canon_sha256":"cd59b268c40ba2a7f1c95c38d07deb2a69e47c55984d9f4218457e722385a81e","abstract_canon_sha256":"d322d899e51d3c4db5607b14ea8519756c2fa5b3c906516c4a542057c52c4196"},"schema_version":"1.0"},"canonical_sha256":"36c757cc113d5b2d7c3eac67bfbe960df84ddd1cef2239e48ff2486821ff13a0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:17:51.411111Z","signature_b64":"Z6YYNUoTHRrSGMbWqrV3lxp8M05V1h/LjJw2PtonYUXDDBUDMR7WXqwSXNWiy+E+2Exrapy5np03SSbvIK3IBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36c757cc113d5b2d7c3eac67bfbe960df84ddd1cef2239e48ff2486821ff13a0","last_reissued_at":"2026-07-05T09:17:51.410701Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:17:51.410701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.04842","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":"2026-07-05T09:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v3mfNRuMy6z4mxN96Jxtc0yhK7G/8k4doAzE6selCTgllb/g46r7pXIrTSRwRDE3K3xDczrt/VqmS5cZKHOfCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:10:28.342114Z"},"content_sha256":"00be05af88e484ecae79da3e6e288b4916edd4e5a4bb67967f721a0bdbb040ca","schema_version":"1.0","event_id":"sha256:00be05af88e484ecae79da3e6e288b4916edd4e5a4bb67967f721a0bdbb040ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:G3DVPTARHVNS27B6VRT37PUWBX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Simple Image Segmentation Framework via In-Context Examples","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chenchen Jing, Chunhua Shen, Hao Chen, Hengtao Li, Muzhi Zhu, Xinlong Wang, Yang Liu","submitted_at":"2024-10-07T08:59:05Z","abstract_excerpt":"Recently, there have been explorations of generalist segmentation models that can effectively tackle a variety of image segmentation tasks within a unified in-context learning framework. However, these methods still struggle with task ambiguity in in-context segmentation, as not all in-context examples can accurately convey the task information. In order to address this issue, we present SINE, a simple image Segmentation framework utilizing in-context examples. Our approach leverages a Transformer encoder-decoder structure, where the encoder provides high-quality image representations, and the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04842","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/2410.04842/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":"2026-07-05T09:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dnVW3ronGVJI+IoJgWfC99KSWnuRd73Q+JrZIWibZPsEOdglaeLMb6SCCszPWgU6+fIyR9pN/znlFvCSbFGMDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:10:28.342624Z"},"content_sha256":"c04d4ccfaee147d4a902373fea78249b5b60eca46a13a9f52842ac65786af68c","schema_version":"1.0","event_id":"sha256:c04d4ccfaee147d4a902373fea78249b5b60eca46a13a9f52842ac65786af68c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G3DVPTARHVNS27B6VRT37PUWBX/bundle.json","state_url":"https://pith.science/pith/G3DVPTARHVNS27B6VRT37PUWBX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G3DVPTARHVNS27B6VRT37PUWBX/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":"2026-08-06T19:10:28Z","links":{"resolver":"https://pith.science/pith/G3DVPTARHVNS27B6VRT37PUWBX","bundle":"https://pith.science/pith/G3DVPTARHVNS27B6VRT37PUWBX/bundle.json","state":"https://pith.science/pith/G3DVPTARHVNS27B6VRT37PUWBX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G3DVPTARHVNS27B6VRT37PUWBX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:G3DVPTARHVNS27B6VRT37PUWBX","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":"d322d899e51d3c4db5607b14ea8519756c2fa5b3c906516c4a542057c52c4196","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-07T08:59:05Z","title_canon_sha256":"cd59b268c40ba2a7f1c95c38d07deb2a69e47c55984d9f4218457e722385a81e"},"schema_version":"1.0","source":{"id":"2410.04842","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04842","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04842v2","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04842","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"G3DVPTARHVNS","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"G3DVPTARHVNS27B6","created_at":"2026-07-05T09:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"G3DVPTAR","created_at":"2026-07-05T09:17:51Z"}],"graph_snapshots":[{"event_id":"sha256:c04d4ccfaee147d4a902373fea78249b5b60eca46a13a9f52842ac65786af68c","target":"graph","created_at":"2026-07-05T09:17:51Z","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/2410.04842/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, there have been explorations of generalist segmentation models that can effectively tackle a variety of image segmentation tasks within a unified in-context learning framework. However, these methods still struggle with task ambiguity in in-context segmentation, as not all in-context examples can accurately convey the task information. In order to address this issue, we present SINE, a simple image Segmentation framework utilizing in-context examples. Our approach leverages a Transformer encoder-decoder structure, where the encoder provides high-quality image representations, and the","authors_text":"Chenchen Jing, Chunhua Shen, Hao Chen, Hengtao Li, Muzhi Zhu, Xinlong Wang, Yang Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-07T08:59:05Z","title":"A Simple Image Segmentation Framework via In-Context Examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04842","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":"sha256:00be05af88e484ecae79da3e6e288b4916edd4e5a4bb67967f721a0bdbb040ca","target":"record","created_at":"2026-07-05T09:17:51Z","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":"d322d899e51d3c4db5607b14ea8519756c2fa5b3c906516c4a542057c52c4196","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-07T08:59:05Z","title_canon_sha256":"cd59b268c40ba2a7f1c95c38d07deb2a69e47c55984d9f4218457e722385a81e"},"schema_version":"1.0","source":{"id":"2410.04842","kind":"arxiv","version":2}},"canonical_sha256":"36c757cc113d5b2d7c3eac67bfbe960df84ddd1cef2239e48ff2486821ff13a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36c757cc113d5b2d7c3eac67bfbe960df84ddd1cef2239e48ff2486821ff13a0","first_computed_at":"2026-07-05T09:17:51.410701Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:17:51.410701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z6YYNUoTHRrSGMbWqrV3lxp8M05V1h/LjJw2PtonYUXDDBUDMR7WXqwSXNWiy+E+2Exrapy5np03SSbvIK3IBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:17:51.411111Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04842","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:00be05af88e484ecae79da3e6e288b4916edd4e5a4bb67967f721a0bdbb040ca","sha256:c04d4ccfaee147d4a902373fea78249b5b60eca46a13a9f52842ac65786af68c"],"state_sha256":"c83ca548440fefef17648e83bf71e868339a0aa7bc8ac153eb8d2b7df78053d9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SbIbUiDWRqpZxSlrxBxGjYBlQ9nPmDWYW30iDjGRRn/ioEPDFJjOnWBgvz35BWix2k49h9PZTVzfzfJ0F+EOBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:10:28.346485Z","bundle_sha256":"c86c077d9ea9a1e95e31a70c4445e5609b476bf10dd9320657a469effd70471e"}}