{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IKCDII7QJ76TC55UFPPHQ2NCQP","short_pith_number":"pith:IKCDII7Q","canonical_record":{"source":{"id":"2307.12519","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-24T04:29:00Z","cross_cats_sorted":[],"title_canon_sha256":"82eeb186ebcb9437e4a097b94ef0eeafc7a9589dc3ba8c0a20c7172f6a560b1d","abstract_canon_sha256":"1095f418736ff50e25712ca6d849f2ce037a28dd8daaf9c700d29df224c9037f"},"schema_version":"1.0"},"canonical_sha256":"42843423f04ffd3177b42bde7869a283f538e8d58dad719369195510add83bd5","source":{"kind":"arxiv","id":"2307.12519","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.12519","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"arxiv_version","alias_value":"2307.12519v1","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.12519","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_12","alias_value":"IKCDII7QJ76T","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_16","alias_value":"IKCDII7QJ76TC55U","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_8","alias_value":"IKCDII7Q","created_at":"2026-07-05T06:33:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IKCDII7QJ76TC55UFPPHQ2NCQP","target":"record","payload":{"canonical_record":{"source":{"id":"2307.12519","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-24T04:29:00Z","cross_cats_sorted":[],"title_canon_sha256":"82eeb186ebcb9437e4a097b94ef0eeafc7a9589dc3ba8c0a20c7172f6a560b1d","abstract_canon_sha256":"1095f418736ff50e25712ca6d849f2ce037a28dd8daaf9c700d29df224c9037f"},"schema_version":"1.0"},"canonical_sha256":"42843423f04ffd3177b42bde7869a283f538e8d58dad719369195510add83bd5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:33:55.100651Z","signature_b64":"JrvTgmo0IXcxV5c1CQCmq8zRwJLyS0IRoRheGgOu2o+a7QYVcev2nN/GCZbFa90+ALfrA6kB8NpKJDQt+ugJBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"42843423f04ffd3177b42bde7869a283f538e8d58dad719369195510add83bd5","last_reissued_at":"2026-07-05T06:33:55.100177Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:33:55.100177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.12519","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":"2026-07-05T06:33:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cn41Z7KC+pmACEnEDIMxa+4cRZR3BSlHHqPCLCr0MXqVPr+fkValCljjk4OFmhNheU6hvobvWtCrN5Uw4Ib9BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T20:51:09.076301Z"},"content_sha256":"c24f5c6cd32e3d08f14115dfd098a45967630c6e0014aeec22b8809e40c90fd1","schema_version":"1.0","event_id":"sha256:c24f5c6cd32e3d08f14115dfd098a45967630c6e0014aeec22b8809e40c90fd1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IKCDII7QJ76TC55UFPPHQ2NCQP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Menglin Kong, Muzhou Hou, Ri Su, Shaojie Zhao","submitted_at":"2023-07-24T04:29:00Z","abstract_excerpt":"Recommendation system algorithm based on multi-task learning (MTL) is the major method for Internet operators to understand users and predict their behaviors in the multi-behavior scenario of platform. Task correlation is an important consideration of MTL goals, traditional models use shared-bottom models and gating experts to realize shared representation learning and information differentiation. However, The relationship between real-world tasks is often more complex than existing methods do not handle properly sharing information. In this paper, we propose an Different Expression Parallel H"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.12519","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/2307.12519/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":"2026-07-05T06:33:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A0HBQ4prhyJ/GZxYYoGDLuCUFNo4pI1XoLIpO4M65Oqk0BuLkuwMxCJjjsSMpYa5d0CpuRM0v7FsvTfxDxYmDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T20:51:09.076701Z"},"content_sha256":"8a536ddb2be12910b768d0a11bd48d15646e0ff3c7e0e3a471311115ebf78204","schema_version":"1.0","event_id":"sha256:8a536ddb2be12910b768d0a11bd48d15646e0ff3c7e0e3a471311115ebf78204"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/bundle.json","state_url":"https://pith.science/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/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":"2026-07-08T20:51:09Z","links":{"resolver":"https://pith.science/pith/IKCDII7QJ76TC55UFPPHQ2NCQP","bundle":"https://pith.science/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/bundle.json","state":"https://pith.science/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IKCDII7QJ76TC55UFPPHQ2NCQP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IKCDII7QJ76TC55UFPPHQ2NCQP","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":"1095f418736ff50e25712ca6d849f2ce037a28dd8daaf9c700d29df224c9037f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-24T04:29:00Z","title_canon_sha256":"82eeb186ebcb9437e4a097b94ef0eeafc7a9589dc3ba8c0a20c7172f6a560b1d"},"schema_version":"1.0","source":{"id":"2307.12519","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.12519","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"arxiv_version","alias_value":"2307.12519v1","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.12519","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_12","alias_value":"IKCDII7QJ76T","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_16","alias_value":"IKCDII7QJ76TC55U","created_at":"2026-07-05T06:33:55Z"},{"alias_kind":"pith_short_8","alias_value":"IKCDII7Q","created_at":"2026-07-05T06:33:55Z"}],"graph_snapshots":[{"event_id":"sha256:8a536ddb2be12910b768d0a11bd48d15646e0ff3c7e0e3a471311115ebf78204","target":"graph","created_at":"2026-07-05T06:33:55Z","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/2307.12519/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recommendation system algorithm based on multi-task learning (MTL) is the major method for Internet operators to understand users and predict their behaviors in the multi-behavior scenario of platform. Task correlation is an important consideration of MTL goals, traditional models use shared-bottom models and gating experts to realize shared representation learning and information differentiation. However, The relationship between real-world tasks is often more complex than existing methods do not handle properly sharing information. In this paper, we propose an Different Expression Parallel H","authors_text":"Menglin Kong, Muzhou Hou, Ri Su, Shaojie Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-24T04:29:00Z","title":"DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.12519","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:c24f5c6cd32e3d08f14115dfd098a45967630c6e0014aeec22b8809e40c90fd1","target":"record","created_at":"2026-07-05T06:33:55Z","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":"1095f418736ff50e25712ca6d849f2ce037a28dd8daaf9c700d29df224c9037f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-24T04:29:00Z","title_canon_sha256":"82eeb186ebcb9437e4a097b94ef0eeafc7a9589dc3ba8c0a20c7172f6a560b1d"},"schema_version":"1.0","source":{"id":"2307.12519","kind":"arxiv","version":1}},"canonical_sha256":"42843423f04ffd3177b42bde7869a283f538e8d58dad719369195510add83bd5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"42843423f04ffd3177b42bde7869a283f538e8d58dad719369195510add83bd5","first_computed_at":"2026-07-05T06:33:55.100177Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:33:55.100177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JrvTgmo0IXcxV5c1CQCmq8zRwJLyS0IRoRheGgOu2o+a7QYVcev2nN/GCZbFa90+ALfrA6kB8NpKJDQt+ugJBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:33:55.100651Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.12519","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c24f5c6cd32e3d08f14115dfd098a45967630c6e0014aeec22b8809e40c90fd1","sha256:8a536ddb2be12910b768d0a11bd48d15646e0ff3c7e0e3a471311115ebf78204"],"state_sha256":"33135d5655f2336e6c392a849aa06889d505f164f80ea25f27dd13bc5ad43065"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UxcWDkQHEduOpyapIB9r6nC37ap75oK8VEU2yMYkat7efKGKfwnlQfNUH/owvR0rpGIOY3+3VINHAQXSWw3gAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T20:51:09.078699Z","bundle_sha256":"6bc2d76721f1e2e91aec43afd13d1e315555bde07ee6201944574b369ec9f937"}}