{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:F5CF5BHSDPYNWQH6DKZTD5WZIK","short_pith_number":"pith:F5CF5BHS","canonical_record":{"source":{"id":"1812.06378","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-16T02:44:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3cd8b2c7a89f8b7c8757a31e821a9f82a8498d9b0db290838835dbd8c4f14702","abstract_canon_sha256":"17779f1ae8a87144fd21d34fed7794a051461da4f9d07bbb939607cd3aad076f"},"schema_version":"1.0"},"canonical_sha256":"2f445e84f21bf0db40fe1ab331f6d942bb2dadab0116ca309da25647c0fc2303","source":{"kind":"arxiv","id":"1812.06378","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.06378","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"arxiv_version","alias_value":"1812.06378v1","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.06378","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"pith_short_12","alias_value":"F5CF5BHSDPYN","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"F5CF5BHSDPYNWQH6","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"F5CF5BHS","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:F5CF5BHSDPYNWQH6DKZTD5WZIK","target":"record","payload":{"canonical_record":{"source":{"id":"1812.06378","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-16T02:44:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3cd8b2c7a89f8b7c8757a31e821a9f82a8498d9b0db290838835dbd8c4f14702","abstract_canon_sha256":"17779f1ae8a87144fd21d34fed7794a051461da4f9d07bbb939607cd3aad076f"},"schema_version":"1.0"},"canonical_sha256":"2f445e84f21bf0db40fe1ab331f6d942bb2dadab0116ca309da25647c0fc2303","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:10.409374Z","signature_b64":"2dK+UEiQ0/AW294yzw5X/XEqD6Zf+ejIUVUODRtry3+EKtsU+cvW40xvyJ72GjkpZMRE1EznxGHPzBsXK4v7DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2f445e84f21bf0db40fe1ab331f6d942bb2dadab0116ca309da25647c0fc2303","last_reissued_at":"2026-05-17T23:58:10.408884Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:10.408884Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.06378","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":"2026-05-17T23:58:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"274akPzIcQ3UakWy7wnmxFIseqJ03Yhm9VxWzWP76DIfMS+7JEnCByC8Wo0wzDQG5KFuKUi8qeHu5JVrAoSDDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T23:00:40.563219Z"},"content_sha256":"b4dc35e2ca7de5e858f29b3112ac05a4398610df84e3db621c0dc0d40d539cb8","schema_version":"1.0","event_id":"sha256:b4dc35e2ca7de5e858f29b3112ac05a4398610df84e3db621c0dc0d40d539cb8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:F5CF5BHSDPYNWQH6DKZTD5WZIK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Super Resolution Using Binarized Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Hongyu Xiong, Lizhuang Ma, Yinglan Ma, Zhe Hu","submitted_at":"2018-12-16T02:44:20Z","abstract_excerpt":"Deep convolutional neural networks (DCNNs) have recently demonstrated high-quality results in single-image super-resolution (SR). DCNNs often suffer from over-parametrization and large amounts of redundancy, which results in inefficient inference and high memory usage, preventing massive applications on mobile devices. As a way to significantly reduce model size and computation time, binarized neural network has only been shown to excel on semantic-level tasks such as image classification and recognition. However, little effort of network quantization has been spent on image enhancement tasks "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.06378","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":""},"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":"2026-05-17T23:58:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VPeGZ4y95dfmoWoNAki2CuDYHsG6iX7d6X/of9BlT3vS1+tCCJSaN9bqxl8MLv1I+tPgOfCEJDSpeVR4LZ4XBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T23:00:40.563634Z"},"content_sha256":"7725c78c98d665ab1a19bfa129724b68a256a91dd02e014ca2e8f8dad79237e7","schema_version":"1.0","event_id":"sha256:7725c78c98d665ab1a19bfa129724b68a256a91dd02e014ca2e8f8dad79237e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/bundle.json","state_url":"https://pith.science/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/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":"2026-05-23T23:00:40Z","links":{"resolver":"https://pith.science/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK","bundle":"https://pith.science/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/bundle.json","state":"https://pith.science/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F5CF5BHSDPYNWQH6DKZTD5WZIK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:F5CF5BHSDPYNWQH6DKZTD5WZIK","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":"17779f1ae8a87144fd21d34fed7794a051461da4f9d07bbb939607cd3aad076f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-16T02:44:20Z","title_canon_sha256":"3cd8b2c7a89f8b7c8757a31e821a9f82a8498d9b0db290838835dbd8c4f14702"},"schema_version":"1.0","source":{"id":"1812.06378","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.06378","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"arxiv_version","alias_value":"1812.06378v1","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.06378","created_at":"2026-05-17T23:58:10Z"},{"alias_kind":"pith_short_12","alias_value":"F5CF5BHSDPYN","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"F5CF5BHSDPYNWQH6","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"F5CF5BHS","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:7725c78c98d665ab1a19bfa129724b68a256a91dd02e014ca2e8f8dad79237e7","target":"graph","created_at":"2026-05-17T23:58:10Z","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"},"paper":{"abstract_excerpt":"Deep convolutional neural networks (DCNNs) have recently demonstrated high-quality results in single-image super-resolution (SR). DCNNs often suffer from over-parametrization and large amounts of redundancy, which results in inefficient inference and high memory usage, preventing massive applications on mobile devices. As a way to significantly reduce model size and computation time, binarized neural network has only been shown to excel on semantic-level tasks such as image classification and recognition. However, little effort of network quantization has been spent on image enhancement tasks ","authors_text":"Hongyu Xiong, Lizhuang Ma, Yinglan Ma, Zhe Hu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-16T02:44:20Z","title":"Efficient Super Resolution Using Binarized Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.06378","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:b4dc35e2ca7de5e858f29b3112ac05a4398610df84e3db621c0dc0d40d539cb8","target":"record","created_at":"2026-05-17T23:58:10Z","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":"17779f1ae8a87144fd21d34fed7794a051461da4f9d07bbb939607cd3aad076f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-16T02:44:20Z","title_canon_sha256":"3cd8b2c7a89f8b7c8757a31e821a9f82a8498d9b0db290838835dbd8c4f14702"},"schema_version":"1.0","source":{"id":"1812.06378","kind":"arxiv","version":1}},"canonical_sha256":"2f445e84f21bf0db40fe1ab331f6d942bb2dadab0116ca309da25647c0fc2303","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2f445e84f21bf0db40fe1ab331f6d942bb2dadab0116ca309da25647c0fc2303","first_computed_at":"2026-05-17T23:58:10.408884Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:10.408884Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2dK+UEiQ0/AW294yzw5X/XEqD6Zf+ejIUVUODRtry3+EKtsU+cvW40xvyJ72GjkpZMRE1EznxGHPzBsXK4v7DQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:10.409374Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.06378","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4dc35e2ca7de5e858f29b3112ac05a4398610df84e3db621c0dc0d40d539cb8","sha256:7725c78c98d665ab1a19bfa129724b68a256a91dd02e014ca2e8f8dad79237e7"],"state_sha256":"3ce23d82d26574a39cbe2ae271e819c3037a81a929faf5b781f8572c51805cd4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HgIstZGtv5uGepzqXK/FQv1xpLWMF8GIwKLMznrwbnpohhS6g1f1KuFllf6OqMAb9tuQ/Ehg+1eFDNGwFsn9Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T23:00:40.567458Z","bundle_sha256":"c099555cedadb2d2b72c68483862f70ef8b105eb24c249eabd08266cf1d33719"}}