{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7Y4ECRC2MBGU23T3SNZALX5YSH","short_pith_number":"pith:7Y4ECRC2","canonical_record":{"source":{"id":"2302.03431","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.IR","submitted_at":"2023-02-07T12:34:31Z","cross_cats_sorted":[],"title_canon_sha256":"31f71663b11e19bd9942a8d01cc045bb9d0e6c3bde5e6d3e21e12436b30e7be4","abstract_canon_sha256":"5c794b06276e75669788c7dd3a93017a2b9493b0f67615238098ea5002e4d253"},"schema_version":"1.0"},"canonical_sha256":"fe3841445a604d4d6e7b937205dfb891e2e1f9b5d4311cb09334667b2b56afab","source":{"kind":"arxiv","id":"2302.03431","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.03431","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"arxiv_version","alias_value":"2302.03431v2","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03431","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_12","alias_value":"7Y4ECRC2MBGU","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_16","alias_value":"7Y4ECRC2MBGU23T3","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_8","alias_value":"7Y4ECRC2","created_at":"2026-07-05T05:39:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7Y4ECRC2MBGU23T3SNZALX5YSH","target":"record","payload":{"canonical_record":{"source":{"id":"2302.03431","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.IR","submitted_at":"2023-02-07T12:34:31Z","cross_cats_sorted":[],"title_canon_sha256":"31f71663b11e19bd9942a8d01cc045bb9d0e6c3bde5e6d3e21e12436b30e7be4","abstract_canon_sha256":"5c794b06276e75669788c7dd3a93017a2b9493b0f67615238098ea5002e4d253"},"schema_version":"1.0"},"canonical_sha256":"fe3841445a604d4d6e7b937205dfb891e2e1f9b5d4311cb09334667b2b56afab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:39:56.468915Z","signature_b64":"qYHfhvwTFXYKiaUEWmKDiIudnjVSvNU56dxNKSRkp0vAWLmayxymBW6GqPBiN/dwK1SFNPa3w3vSlSJlfeR/CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe3841445a604d4d6e7b937205dfb891e2e1f9b5d4311cb09334667b2b56afab","last_reissued_at":"2026-07-05T05:39:56.468465Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:39:56.468465Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.03431","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":"2026-07-05T05:39:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pTnPiJlAfQVm9mBVCjH9amtHMrfc0rdYLrRa9L6b0Ty6lf1oWZJUELsCgDSUGHki8ctcbiI+VZ6p8/2pASJtCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:34:45.937588Z"},"content_sha256":"abe201d20f978b856640c6da60fde123731cccd4c58490673a179443015139da","schema_version":"1.0","event_id":"sha256:abe201d20f978b856640c6da60fde123731cccd4c58490673a179443015139da"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7Y4ECRC2MBGU23T3SNZALX5YSH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploration and Regularization of the Latent Action Space in Recommendation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Bowen Sun, Dong Zheng, Ji Jiang, Kun Gai, Peng Jiang, Qingpeng Cai, Shuchang Liu, Xiangyu Zhao, Yongfeng Zhang, Yuhao Wang","submitted_at":"2023-02-07T12:34:31Z","abstract_excerpt":"In recommender systems, reinforcement learning solutions have effectively boosted recommendation performance because of their ability to capture long-term user-system interaction. However, the action space of the recommendation policy is a list of items, which could be extremely large with a dynamic candidate item pool. To overcome this challenge, we propose a hyper-actor and critic learning framework where the policy decomposes the item list generation process into a hyper-action inference step and an effect-action selection step. The first step maps the given state space into a vectorized hy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03431","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/2302.03431/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":"2026-07-05T05:39:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1TXtxfYpEUBfH6nacGfBBkTQJR4Nedtnvvwt+I5KYxR7C8k26yN+qwFztJ5fYfTwAji9x/OIvvATNg+OMor7BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:34:45.938079Z"},"content_sha256":"5248528590c78a1286d9a57c5104da0b1300eda932a3fc4549d8ccf7444705cf","schema_version":"1.0","event_id":"sha256:5248528590c78a1286d9a57c5104da0b1300eda932a3fc4549d8ccf7444705cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/bundle.json","state_url":"https://pith.science/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/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":"2026-08-07T07:34:45Z","links":{"resolver":"https://pith.science/pith/7Y4ECRC2MBGU23T3SNZALX5YSH","bundle":"https://pith.science/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/bundle.json","state":"https://pith.science/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7Y4ECRC2MBGU23T3SNZALX5YSH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7Y4ECRC2MBGU23T3SNZALX5YSH","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":"5c794b06276e75669788c7dd3a93017a2b9493b0f67615238098ea5002e4d253","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.IR","submitted_at":"2023-02-07T12:34:31Z","title_canon_sha256":"31f71663b11e19bd9942a8d01cc045bb9d0e6c3bde5e6d3e21e12436b30e7be4"},"schema_version":"1.0","source":{"id":"2302.03431","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.03431","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"arxiv_version","alias_value":"2302.03431v2","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03431","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_12","alias_value":"7Y4ECRC2MBGU","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_16","alias_value":"7Y4ECRC2MBGU23T3","created_at":"2026-07-05T05:39:56Z"},{"alias_kind":"pith_short_8","alias_value":"7Y4ECRC2","created_at":"2026-07-05T05:39:56Z"}],"graph_snapshots":[{"event_id":"sha256:5248528590c78a1286d9a57c5104da0b1300eda932a3fc4549d8ccf7444705cf","target":"graph","created_at":"2026-07-05T05:39:56Z","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/2302.03431/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recommender systems, reinforcement learning solutions have effectively boosted recommendation performance because of their ability to capture long-term user-system interaction. However, the action space of the recommendation policy is a list of items, which could be extremely large with a dynamic candidate item pool. To overcome this challenge, we propose a hyper-actor and critic learning framework where the policy decomposes the item list generation process into a hyper-action inference step and an effect-action selection step. The first step maps the given state space into a vectorized hy","authors_text":"Bowen Sun, Dong Zheng, Ji Jiang, Kun Gai, Peng Jiang, Qingpeng Cai, Shuchang Liu, Xiangyu Zhao, Yongfeng Zhang, Yuhao Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.IR","submitted_at":"2023-02-07T12:34:31Z","title":"Exploration and Regularization of the Latent Action Space in Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03431","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:abe201d20f978b856640c6da60fde123731cccd4c58490673a179443015139da","target":"record","created_at":"2026-07-05T05:39:56Z","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":"5c794b06276e75669788c7dd3a93017a2b9493b0f67615238098ea5002e4d253","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.IR","submitted_at":"2023-02-07T12:34:31Z","title_canon_sha256":"31f71663b11e19bd9942a8d01cc045bb9d0e6c3bde5e6d3e21e12436b30e7be4"},"schema_version":"1.0","source":{"id":"2302.03431","kind":"arxiv","version":2}},"canonical_sha256":"fe3841445a604d4d6e7b937205dfb891e2e1f9b5d4311cb09334667b2b56afab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe3841445a604d4d6e7b937205dfb891e2e1f9b5d4311cb09334667b2b56afab","first_computed_at":"2026-07-05T05:39:56.468465Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:39:56.468465Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qYHfhvwTFXYKiaUEWmKDiIudnjVSvNU56dxNKSRkp0vAWLmayxymBW6GqPBiN/dwK1SFNPa3w3vSlSJlfeR/CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:39:56.468915Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.03431","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:abe201d20f978b856640c6da60fde123731cccd4c58490673a179443015139da","sha256:5248528590c78a1286d9a57c5104da0b1300eda932a3fc4549d8ccf7444705cf"],"state_sha256":"ef6a47e859723a3fe30328a1583c3acea6e9758e13d4b32f0fc5f71e3446f350"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/IGvSZdq0SPRWaGXLQqrX8GP591r0/mojN0Q6C+ndpMioQYgh2Il2yTY9Z4UU1KWJzLm0GRLsw5ckQr+JVXyBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T07:34:45.942069Z","bundle_sha256":"811d508cec77fd10bb2b7057f7744485cca7aa707f09cf8fb52d7c53031f95dc"}}