{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CM2Q25TAGGPXOXBNYWW2GLZ2MV","short_pith_number":"pith:CM2Q25TA","canonical_record":{"source":{"id":"2408.17214","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-08-30T11:38:51Z","cross_cats_sorted":[],"title_canon_sha256":"77f519486c84ce4b68390900ccebf8001984780891e141907b20c2522bb54530","abstract_canon_sha256":"54000478a6c72359eae359427407c6758cdb07964c1a1c28a192b8b228e47b7c"},"schema_version":"1.0"},"canonical_sha256":"13350d7660319f775c2dc5ada32f3a65660003324f4314205f7d06dde5235cbe","source":{"kind":"arxiv","id":"2408.17214","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17214","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17214v1","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17214","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_12","alias_value":"CM2Q25TAGGPX","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_16","alias_value":"CM2Q25TAGGPXOXBN","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_8","alias_value":"CM2Q25TA","created_at":"2026-07-05T09:01:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CM2Q25TAGGPXOXBNYWW2GLZ2MV","target":"record","payload":{"canonical_record":{"source":{"id":"2408.17214","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-08-30T11:38:51Z","cross_cats_sorted":[],"title_canon_sha256":"77f519486c84ce4b68390900ccebf8001984780891e141907b20c2522bb54530","abstract_canon_sha256":"54000478a6c72359eae359427407c6758cdb07964c1a1c28a192b8b228e47b7c"},"schema_version":"1.0"},"canonical_sha256":"13350d7660319f775c2dc5ada32f3a65660003324f4314205f7d06dde5235cbe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:01:12.327901Z","signature_b64":"3X+Wp6ynm7j6Lwceys76zhAH2JcFyYrb09tB0vdzkvYL7A8t8llNM11pK4uzW4HW9ee0ThQmHHCKiN12NaJnAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13350d7660319f775c2dc5ada32f3a65660003324f4314205f7d06dde5235cbe","last_reissued_at":"2026-07-05T09:01:12.327423Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:01:12.327423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.17214","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":"2026-07-05T09:01:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N+2WpbraGo2M/MO2dhhZyciOdH1798N7qdLoOGmp87BfJdiTqcE5rCw0jG8y0a9x78YGfsDxEtxWgB9VwI2oDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:33:06.217145Z"},"content_sha256":"e986cfd077b0fe4b59c4553affc52603f9aa8b881e1a90cadabc1630c118ec18","schema_version":"1.0","event_id":"sha256:e986cfd077b0fe4b59c4553affc52603f9aa8b881e1a90cadabc1630c118ec18"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CM2Q25TAGGPXOXBNYWW2GLZ2MV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Multi-task Prompt Tuning for Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Cheng Hou, Cheng Yang, Chuan Shi, Le Huang, Ting Bai, Yue Yu, Zhe Zhao","submitted_at":"2024-08-30T11:38:51Z","abstract_excerpt":"With the expansion of business scenarios, real recommender systems are facing challenges in dealing with the constantly emerging new tasks in multi-task learning frameworks. In this paper, we attempt to improve the generalization ability of multi-task recommendations when dealing with new tasks. We find that joint training will enhance the performance of the new task but always negatively impact existing tasks in most multi-task learning methods. Besides, such a re-training mechanism with new tasks increases the training costs, limiting the generalization ability of multi-task recommendation m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17214","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/2408.17214/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":"2026-07-05T09:01:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7yT2xPvXylsHwq74GyH1AfGkNiCRjwnfq3w0QqidYN9WJXsRiwr9MG+Tjs6Ht5TVsy7cu3tHVLgL+iEJdAi3Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:33:06.217682Z"},"content_sha256":"1a330daac4150cb74c2a1dee1d4d4b58f328b68b5eb1e96495ab499da2ddd4cf","schema_version":"1.0","event_id":"sha256:1a330daac4150cb74c2a1dee1d4d4b58f328b68b5eb1e96495ab499da2ddd4cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/bundle.json","state_url":"https://pith.science/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/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":"2026-08-06T09:33:06Z","links":{"resolver":"https://pith.science/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV","bundle":"https://pith.science/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/bundle.json","state":"https://pith.science/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CM2Q25TAGGPXOXBNYWW2GLZ2MV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CM2Q25TAGGPXOXBNYWW2GLZ2MV","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":"54000478a6c72359eae359427407c6758cdb07964c1a1c28a192b8b228e47b7c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-08-30T11:38:51Z","title_canon_sha256":"77f519486c84ce4b68390900ccebf8001984780891e141907b20c2522bb54530"},"schema_version":"1.0","source":{"id":"2408.17214","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17214","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17214v1","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17214","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_12","alias_value":"CM2Q25TAGGPX","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_16","alias_value":"CM2Q25TAGGPXOXBN","created_at":"2026-07-05T09:01:12Z"},{"alias_kind":"pith_short_8","alias_value":"CM2Q25TA","created_at":"2026-07-05T09:01:12Z"}],"graph_snapshots":[{"event_id":"sha256:1a330daac4150cb74c2a1dee1d4d4b58f328b68b5eb1e96495ab499da2ddd4cf","target":"graph","created_at":"2026-07-05T09:01:12Z","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/2408.17214/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the expansion of business scenarios, real recommender systems are facing challenges in dealing with the constantly emerging new tasks in multi-task learning frameworks. In this paper, we attempt to improve the generalization ability of multi-task recommendations when dealing with new tasks. We find that joint training will enhance the performance of the new task but always negatively impact existing tasks in most multi-task learning methods. Besides, such a re-training mechanism with new tasks increases the training costs, limiting the generalization ability of multi-task recommendation m","authors_text":"Cheng Hou, Cheng Yang, Chuan Shi, Le Huang, Ting Bai, Yue Yu, Zhe Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-08-30T11:38:51Z","title":"Efficient Multi-task Prompt Tuning for Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17214","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:e986cfd077b0fe4b59c4553affc52603f9aa8b881e1a90cadabc1630c118ec18","target":"record","created_at":"2026-07-05T09:01:12Z","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":"54000478a6c72359eae359427407c6758cdb07964c1a1c28a192b8b228e47b7c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-08-30T11:38:51Z","title_canon_sha256":"77f519486c84ce4b68390900ccebf8001984780891e141907b20c2522bb54530"},"schema_version":"1.0","source":{"id":"2408.17214","kind":"arxiv","version":1}},"canonical_sha256":"13350d7660319f775c2dc5ada32f3a65660003324f4314205f7d06dde5235cbe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"13350d7660319f775c2dc5ada32f3a65660003324f4314205f7d06dde5235cbe","first_computed_at":"2026-07-05T09:01:12.327423Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:01:12.327423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3X+Wp6ynm7j6Lwceys76zhAH2JcFyYrb09tB0vdzkvYL7A8t8llNM11pK4uzW4HW9ee0ThQmHHCKiN12NaJnAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:01:12.327901Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.17214","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e986cfd077b0fe4b59c4553affc52603f9aa8b881e1a90cadabc1630c118ec18","sha256:1a330daac4150cb74c2a1dee1d4d4b58f328b68b5eb1e96495ab499da2ddd4cf"],"state_sha256":"785ae2ff630e5a3360fe0dbcbf7777aa8b9c22467e4a163c1803055deba86cb5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jMKDM4f3MDucRvLFIrEMrB/cIVw9yjjniBtthjabmh0rQ+/PSZq9fDQ4fj9z8vyxHpIqe/hYlbu+cbNep3d9DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T09:33:06.223082Z","bundle_sha256":"fddea71c9032c793f36275404af157478bc68acf2e7466fb8bbee087adca31ac"}}