{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:XARTZ3NK4UYH44XW3CTOBCSVCW","short_pith_number":"pith:XARTZ3NK","canonical_record":{"source":{"id":"2304.11697","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-23T16:36:13Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"3f3faa889efe20935d429cf6b589780cbe405e4e111ea0c2b31818fa9b9b03a1","abstract_canon_sha256":"3c6bd2c44ace04cca04e80b7a52b639dbe7578ec051450ff9e99f6d321d353d1"},"schema_version":"1.0"},"canonical_sha256":"b8233cedaae5307e72f6d8a6e08a5515b6148b2639c43f97c0e133414cc9be5b","source":{"kind":"arxiv","id":"2304.11697","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.11697","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"arxiv_version","alias_value":"2304.11697v1","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.11697","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_12","alias_value":"XARTZ3NK4UYH","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_16","alias_value":"XARTZ3NK4UYH44XW","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_8","alias_value":"XARTZ3NK","created_at":"2026-07-05T06:03:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:XARTZ3NK4UYH44XW3CTOBCSVCW","target":"record","payload":{"canonical_record":{"source":{"id":"2304.11697","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-23T16:36:13Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"3f3faa889efe20935d429cf6b589780cbe405e4e111ea0c2b31818fa9b9b03a1","abstract_canon_sha256":"3c6bd2c44ace04cca04e80b7a52b639dbe7578ec051450ff9e99f6d321d353d1"},"schema_version":"1.0"},"canonical_sha256":"b8233cedaae5307e72f6d8a6e08a5515b6148b2639c43f97c0e133414cc9be5b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:03:36.015561Z","signature_b64":"tvuxcacXSjDuCtFPsH7I/1Mj57/clOmTr51cszLNEAatD7eH3mJHUhJyrIVJb5/9RfkA7F+gYxWC/OZ5THcjDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8233cedaae5307e72f6d8a6e08a5515b6148b2639c43f97c0e133414cc9be5b","last_reissued_at":"2026-07-05T06:03:36.015139Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:03:36.015139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.11697","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":"2026-07-05T06:03:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OVtsOWSC+JSnXAyqnOp5VvFoCY/9casazku8NNQZqwvkmx3Y5BP4qF7tm2r0gg+FrH9gOYxg/FZvjsYwMDmkAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T00:25:01.301947Z"},"content_sha256":"73553f2868257fc6fc1f746d6ae0faaa9432ddc4cf29dd7a66598e782aad7d74","schema_version":"1.0","event_id":"sha256:73553f2868257fc6fc1f746d6ae0faaa9432ddc4cf29dd7a66598e782aad7d74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:XARTZ3NK4UYH44XW3CTOBCSVCW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Informative Data Selection with Uncertainty for Multi-modal Object Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Dafeng Jin, Huaping Liu, Jun Li, Xin Gao, Xinyu Zhang, Yijin Xiong, Zhenhong Zou, Zhiwei Li","submitted_at":"2023-04-23T16:36:13Z","abstract_excerpt":"Noise has always been nonnegligible trouble in object detection by creating confusion in model reasoning, thereby reducing the informativeness of the data. It can lead to inaccurate recognition due to the shift in the observed pattern, that requires a robust generalization of the models. To implement a general vision model, we need to develop deep learning models that can adaptively select valid information from multi-modal data. This is mainly based on two reasons. Multi-modal learning can break through the inherent defects of single-modal data, and adaptive information selection can reduce c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.11697","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/2304.11697/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":"2026-07-05T06:03:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LR1vAoCQdBiZA05YY7DZ11zpbqCarwkP8uBUscGeHYKiWUe2ZG0OntlmjQfnR5bKOO64nQWDYn2v1v49ZKdKCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T00:25:01.302624Z"},"content_sha256":"758ffb7e75d2538961045e321f1f6a83817f27e5785a95f9b85f06fb5b50b189","schema_version":"1.0","event_id":"sha256:758ffb7e75d2538961045e321f1f6a83817f27e5785a95f9b85f06fb5b50b189"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/bundle.json","state_url":"https://pith.science/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/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":"2026-07-13T00:25:01Z","links":{"resolver":"https://pith.science/pith/XARTZ3NK4UYH44XW3CTOBCSVCW","bundle":"https://pith.science/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/bundle.json","state":"https://pith.science/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XARTZ3NK4UYH44XW3CTOBCSVCW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XARTZ3NK4UYH44XW3CTOBCSVCW","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":"3c6bd2c44ace04cca04e80b7a52b639dbe7578ec051450ff9e99f6d321d353d1","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-23T16:36:13Z","title_canon_sha256":"3f3faa889efe20935d429cf6b589780cbe405e4e111ea0c2b31818fa9b9b03a1"},"schema_version":"1.0","source":{"id":"2304.11697","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.11697","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"arxiv_version","alias_value":"2304.11697v1","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.11697","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_12","alias_value":"XARTZ3NK4UYH","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_16","alias_value":"XARTZ3NK4UYH44XW","created_at":"2026-07-05T06:03:36Z"},{"alias_kind":"pith_short_8","alias_value":"XARTZ3NK","created_at":"2026-07-05T06:03:36Z"}],"graph_snapshots":[{"event_id":"sha256:758ffb7e75d2538961045e321f1f6a83817f27e5785a95f9b85f06fb5b50b189","target":"graph","created_at":"2026-07-05T06:03:36Z","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/2304.11697/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Noise has always been nonnegligible trouble in object detection by creating confusion in model reasoning, thereby reducing the informativeness of the data. It can lead to inaccurate recognition due to the shift in the observed pattern, that requires a robust generalization of the models. To implement a general vision model, we need to develop deep learning models that can adaptively select valid information from multi-modal data. This is mainly based on two reasons. Multi-modal learning can break through the inherent defects of single-modal data, and adaptive information selection can reduce c","authors_text":"Dafeng Jin, Huaping Liu, Jun Li, Xin Gao, Xinyu Zhang, Yijin Xiong, Zhenhong Zou, Zhiwei Li","cross_cats":["eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-23T16:36:13Z","title":"Informative Data Selection with Uncertainty for Multi-modal Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.11697","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":"sha256:73553f2868257fc6fc1f746d6ae0faaa9432ddc4cf29dd7a66598e782aad7d74","target":"record","created_at":"2026-07-05T06:03:36Z","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":"3c6bd2c44ace04cca04e80b7a52b639dbe7578ec051450ff9e99f6d321d353d1","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-23T16:36:13Z","title_canon_sha256":"3f3faa889efe20935d429cf6b589780cbe405e4e111ea0c2b31818fa9b9b03a1"},"schema_version":"1.0","source":{"id":"2304.11697","kind":"arxiv","version":1}},"canonical_sha256":"b8233cedaae5307e72f6d8a6e08a5515b6148b2639c43f97c0e133414cc9be5b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b8233cedaae5307e72f6d8a6e08a5515b6148b2639c43f97c0e133414cc9be5b","first_computed_at":"2026-07-05T06:03:36.015139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:03:36.015139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tvuxcacXSjDuCtFPsH7I/1Mj57/clOmTr51cszLNEAatD7eH3mJHUhJyrIVJb5/9RfkA7F+gYxWC/OZ5THcjDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:03:36.015561Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.11697","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73553f2868257fc6fc1f746d6ae0faaa9432ddc4cf29dd7a66598e782aad7d74","sha256:758ffb7e75d2538961045e321f1f6a83817f27e5785a95f9b85f06fb5b50b189"],"state_sha256":"4cc95be0f94c5c152de4dc9e3e91b704f24668ac5724ec43c479d73663b07d87"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lMe6ZQl+26rUosVVBaoV51XEk3lRb3fUPpYqw5iB6GgRtAp24Ohbp2cgHFSdURYUyGiFEuMcf59a4b5tNQaHDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T00:25:01.305979Z","bundle_sha256":"d8f2dcd39b0eab5517ccf548607da7d15daabb054952024fec8cc88f7aec0409"}}