{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:3P6KI3R4DFS7WJNQPPNMF242TB","short_pith_number":"pith:3P6KI3R4","canonical_record":{"source":{"id":"2203.12121","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T01:30:48Z","cross_cats_sorted":[],"title_canon_sha256":"0f384ab4372a80874e67bce88060e60fcacb5df1348cc567810c851f3c081465","abstract_canon_sha256":"73d6b0c75170fd1e3209e27816001bec9d61ac75869b9a9728f1e49ab5a9d847"},"schema_version":"1.0"},"canonical_sha256":"dbfca46e3c1965fb25b07bdac2eb9a9865107b1585f99b84f9ded4124575e694","source":{"kind":"arxiv","id":"2203.12121","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.12121","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"arxiv_version","alias_value":"2203.12121v2","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.12121","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_12","alias_value":"3P6KI3R4DFS7","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_16","alias_value":"3P6KI3R4DFS7WJNQ","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_8","alias_value":"3P6KI3R4","created_at":"2026-07-05T04:24:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:3P6KI3R4DFS7WJNQPPNMF242TB","target":"record","payload":{"canonical_record":{"source":{"id":"2203.12121","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T01:30:48Z","cross_cats_sorted":[],"title_canon_sha256":"0f384ab4372a80874e67bce88060e60fcacb5df1348cc567810c851f3c081465","abstract_canon_sha256":"73d6b0c75170fd1e3209e27816001bec9d61ac75869b9a9728f1e49ab5a9d847"},"schema_version":"1.0"},"canonical_sha256":"dbfca46e3c1965fb25b07bdac2eb9a9865107b1585f99b84f9ded4124575e694","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:24:25.425406Z","signature_b64":"qaxSmMtVP3fUD/8kiNgfvajvfvNgf6rt8WErRggB9D+9Wi3eqUiPx33yWFXETZLf/J7OJgIjgvOAZm/gmqMnBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbfca46e3c1965fb25b07bdac2eb9a9865107b1585f99b84f9ded4124575e694","last_reissued_at":"2026-07-05T04:24:25.425022Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:24:25.425022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.12121","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":"2026-07-05T04:24:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GOZ6ct2Z628+9xrdAa71vV/nl/aHKwPrydJsWyDKQeI594qsPTzpIJS6u9w1W9oV8JTLIoqMpRqo2sHS+uucAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:31:22.271805Z"},"content_sha256":"42453ca13ffe50091f3e6176036ddac241283d33fb94846bc343330734277c33","schema_version":"1.0","event_id":"sha256:42453ca13ffe50091f3e6176036ddac241283d33fb94846bc343330734277c33"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:3P6KI3R4DFS7WJNQPPNMF242TB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chong Wang, Fengbei Liu, Guansong Pang, Gustavo Carneiro, Johan W Verjans, Yuanhong Chen, Yu Tian, Yuyuan Liu","submitted_at":"2022-03-23T01:30:48Z","abstract_excerpt":"Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially on challenging polyp cases (e.g., small, flat, or partially visible polyps). In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. In particular, we propose a novel convolutional transforme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.12121","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/2203.12121/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":"2026-07-05T04:24:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mEYm+xsseve6UCJoFPYeF0e9yBIqJYOZZSPNu1pUQmfyXqR0VJxQRjVLxKqqhED77tY4oa4BQaOmmwI8kfLfDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:31:22.272676Z"},"content_sha256":"ebd66f03c2fc6b6130dccb1bdba198a44a40059bd826425b7c96d2a7200d789a","schema_version":"1.0","event_id":"sha256:ebd66f03c2fc6b6130dccb1bdba198a44a40059bd826425b7c96d2a7200d789a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3P6KI3R4DFS7WJNQPPNMF242TB/bundle.json","state_url":"https://pith.science/pith/3P6KI3R4DFS7WJNQPPNMF242TB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3P6KI3R4DFS7WJNQPPNMF242TB/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":"2026-08-04T03:31:22Z","links":{"resolver":"https://pith.science/pith/3P6KI3R4DFS7WJNQPPNMF242TB","bundle":"https://pith.science/pith/3P6KI3R4DFS7WJNQPPNMF242TB/bundle.json","state":"https://pith.science/pith/3P6KI3R4DFS7WJNQPPNMF242TB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3P6KI3R4DFS7WJNQPPNMF242TB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:3P6KI3R4DFS7WJNQPPNMF242TB","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":"73d6b0c75170fd1e3209e27816001bec9d61ac75869b9a9728f1e49ab5a9d847","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T01:30:48Z","title_canon_sha256":"0f384ab4372a80874e67bce88060e60fcacb5df1348cc567810c851f3c081465"},"schema_version":"1.0","source":{"id":"2203.12121","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.12121","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"arxiv_version","alias_value":"2203.12121v2","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.12121","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_12","alias_value":"3P6KI3R4DFS7","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_16","alias_value":"3P6KI3R4DFS7WJNQ","created_at":"2026-07-05T04:24:25Z"},{"alias_kind":"pith_short_8","alias_value":"3P6KI3R4","created_at":"2026-07-05T04:24:25Z"}],"graph_snapshots":[{"event_id":"sha256:ebd66f03c2fc6b6130dccb1bdba198a44a40059bd826425b7c96d2a7200d789a","target":"graph","created_at":"2026-07-05T04:24:25Z","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/2203.12121/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially on challenging polyp cases (e.g., small, flat, or partially visible polyps). In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. In particular, we propose a novel convolutional transforme","authors_text":"Chong Wang, Fengbei Liu, Guansong Pang, Gustavo Carneiro, Johan W Verjans, Yuanhong Chen, Yu Tian, Yuyuan Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T01:30:48Z","title":"Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.12121","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":"sha256:42453ca13ffe50091f3e6176036ddac241283d33fb94846bc343330734277c33","target":"record","created_at":"2026-07-05T04:24:25Z","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":"73d6b0c75170fd1e3209e27816001bec9d61ac75869b9a9728f1e49ab5a9d847","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T01:30:48Z","title_canon_sha256":"0f384ab4372a80874e67bce88060e60fcacb5df1348cc567810c851f3c081465"},"schema_version":"1.0","source":{"id":"2203.12121","kind":"arxiv","version":2}},"canonical_sha256":"dbfca46e3c1965fb25b07bdac2eb9a9865107b1585f99b84f9ded4124575e694","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dbfca46e3c1965fb25b07bdac2eb9a9865107b1585f99b84f9ded4124575e694","first_computed_at":"2026-07-05T04:24:25.425022Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:24:25.425022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qaxSmMtVP3fUD/8kiNgfvajvfvNgf6rt8WErRggB9D+9Wi3eqUiPx33yWFXETZLf/J7OJgIjgvOAZm/gmqMnBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:24:25.425406Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.12121","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42453ca13ffe50091f3e6176036ddac241283d33fb94846bc343330734277c33","sha256:ebd66f03c2fc6b6130dccb1bdba198a44a40059bd826425b7c96d2a7200d789a"],"state_sha256":"a5262b0ec1d42119c2c05d551235dd4001ca794d802e5ef14a81682fe31b4a77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NrnIJ1KeOBlFGLuYIg9GB4Vd3GNZZo3Fk4mQib7TQBlh2fl26TwBo4qvwQXYAjnQlsyG19D5cdxIYnJoqNTMAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T03:31:22.279824Z","bundle_sha256":"18328d0834228280affba95682f8d4ee74c7dcfaeb54659ee7b16baa6757d34f"}}