{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:SYNCX2AKLVVLXH45RET3NGYIOE","short_pith_number":"pith:SYNCX2AK","schema_version":"1.0","canonical_sha256":"961a2be80a5d6abb9f9d8927b69b087137dae06234749a8e2e2b28b7f0a9a947","source":{"kind":"arxiv","id":"2401.15188","version":1},"attestation_state":"computed","paper":{"title":"CAREForMe: Contextual Multi-Armed Bandit Recommendation Framework for Mental Health","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bhaskar Krishnamachari, Emily Zhou, Narjes Nourzad, Randye J. Semple, Sheng Yu, Yixue Zhao","submitted_at":"2024-01-26T20:18:25Z","abstract_excerpt":"The COVID-19 pandemic has intensified the urgency for effective and accessible mental health interventions in people's daily lives. Mobile Health (mHealth) solutions, such as AI Chatbots and Mindfulness Apps, have gained traction as they expand beyond traditional clinical settings to support daily life. However, the effectiveness of current mHealth solutions is impeded by the lack of context-awareness, personalization, and modularity to foster their reusability. This paper introduces CAREForMe, a contextual multi-armed bandit (CMAB) recommendation framework for mental health. Designed with con"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2401.15188","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-01-26T20:18:25Z","cross_cats_sorted":[],"title_canon_sha256":"491b69ad98ed09aa3d2aff47f846ed7216bfde65027e21073ec4ba77a980e63b","abstract_canon_sha256":"26a669b1cba4c87d3278f90f01b0a542f757259721748e67d18eaf14919015f5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:12.735095Z","signature_b64":"NwmJvQ6EXpSQ96qi415tuXvBbMDxrTYBMAHXued8zBJApNtjHHkt8CDmW1BuhO4Nqv7RkSOMCgSoXGfuZiouAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"961a2be80a5d6abb9f9d8927b69b087137dae06234749a8e2e2b28b7f0a9a947","last_reissued_at":"2026-07-05T07:38:12.734492Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:12.734492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CAREForMe: Contextual Multi-Armed Bandit Recommendation Framework for Mental Health","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bhaskar Krishnamachari, Emily Zhou, Narjes Nourzad, Randye J. Semple, Sheng Yu, Yixue Zhao","submitted_at":"2024-01-26T20:18:25Z","abstract_excerpt":"The COVID-19 pandemic has intensified the urgency for effective and accessible mental health interventions in people's daily lives. Mobile Health (mHealth) solutions, such as AI Chatbots and Mindfulness Apps, have gained traction as they expand beyond traditional clinical settings to support daily life. However, the effectiveness of current mHealth solutions is impeded by the lack of context-awareness, personalization, and modularity to foster their reusability. This paper introduces CAREForMe, a contextual multi-armed bandit (CMAB) recommendation framework for mental health. Designed with con"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.15188","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/2401.15188/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2401.15188","created_at":"2026-07-05T07:38:12.734551+00:00"},{"alias_kind":"arxiv_version","alias_value":"2401.15188v1","created_at":"2026-07-05T07:38:12.734551+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.15188","created_at":"2026-07-05T07:38:12.734551+00:00"},{"alias_kind":"pith_short_12","alias_value":"SYNCX2AKLVVL","created_at":"2026-07-05T07:38:12.734551+00:00"},{"alias_kind":"pith_short_16","alias_value":"SYNCX2AKLVVLXH45","created_at":"2026-07-05T07:38:12.734551+00:00"},{"alias_kind":"pith_short_8","alias_value":"SYNCX2AK","created_at":"2026-07-05T07:38:12.734551+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2502.08759","citing_title":"Contextual bandits with entropy-based human feedback","ref_index":18,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE","json":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE.json","graph_json":"https://pith.science/api/pith-number/SYNCX2AKLVVLXH45RET3NGYIOE/graph.json","events_json":"https://pith.science/api/pith-number/SYNCX2AKLVVLXH45RET3NGYIOE/events.json","paper":"https://pith.science/paper/SYNCX2AK"},"agent_actions":{"view_html":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE","download_json":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE.json","view_paper":"https://pith.science/paper/SYNCX2AK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2401.15188&json=true","fetch_graph":"https://pith.science/api/pith-number/SYNCX2AKLVVLXH45RET3NGYIOE/graph.json","fetch_events":"https://pith.science/api/pith-number/SYNCX2AKLVVLXH45RET3NGYIOE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE/action/storage_attestation","attest_author":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE/action/author_attestation","sign_citation":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE/action/citation_signature","submit_replication":"https://pith.science/pith/SYNCX2AKLVVLXH45RET3NGYIOE/action/replication_record"}},"created_at":"2026-07-05T07:38:12.734551+00:00","updated_at":"2026-07-05T07:38:12.734551+00:00"}