{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MBWMF4UJHZTZXIXJIM2KHZPEBN","short_pith_number":"pith:MBWMF4UJ","canonical_record":{"source":{"id":"2506.21931","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-27T05:45:59Z","cross_cats_sorted":["cs.AI","cs.CL","cs.MA"],"title_canon_sha256":"5204c2c0203d47d962ba990c2e849f844765227b6b5fe8545f92938cb07a9eac","abstract_canon_sha256":"baa9b24a9c7b490caf2fe84d08883d193add7c5e77a357a2303acba6ba4787be"},"schema_version":"1.0"},"canonical_sha256":"606cc2f2893e679ba2e94334a3e5e40b67be6d7d813b048d12b868bfe218a13a","source":{"kind":"arxiv","id":"2506.21931","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21931","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21931v2","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21931","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_12","alias_value":"MBWMF4UJHZTZ","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_16","alias_value":"MBWMF4UJHZTZXIXJ","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_8","alias_value":"MBWMF4UJ","created_at":"2026-07-05T11:52:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MBWMF4UJHZTZXIXJIM2KHZPEBN","target":"record","payload":{"canonical_record":{"source":{"id":"2506.21931","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-27T05:45:59Z","cross_cats_sorted":["cs.AI","cs.CL","cs.MA"],"title_canon_sha256":"5204c2c0203d47d962ba990c2e849f844765227b6b5fe8545f92938cb07a9eac","abstract_canon_sha256":"baa9b24a9c7b490caf2fe84d08883d193add7c5e77a357a2303acba6ba4787be"},"schema_version":"1.0"},"canonical_sha256":"606cc2f2893e679ba2e94334a3e5e40b67be6d7d813b048d12b868bfe218a13a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:02.990922Z","signature_b64":"xYDeObbLqz8DsWt2lhNpqx1it3Q/L2e++2MjzYRn7dMXBuNWCGz2hXqGQs/8N7XmOr1ytbFyVKyPTl7KX2yQAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"606cc2f2893e679ba2e94334a3e5e40b67be6d7d813b048d12b868bfe218a13a","last_reissued_at":"2026-07-05T11:52:02.990393Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:02.990393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.21931","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":"2026-07-05T11:52:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RI9HPocgiRneskZR70zT5cfxogcwTxHPE+YRudSdcR448kK9WzSjC5gqBrj6dRDKfsZCrlecYK/eUo44iQH1Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:34:06.288676Z"},"content_sha256":"c89c03585d712765437c7f77adecf5da388b9d2db12eb0778cbed2f11130afe3","schema_version":"1.0","event_id":"sha256:c89c03585d712765437c7f77adecf5da388b9d2db12eb0778cbed2f11130afe3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MBWMF4UJHZTZXIXJIM2KHZPEBN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.MA"],"primary_cat":"cs.IR","authors_text":"Aysenur Inan, Jason Cho, Jianpeng Xu, Kai Zhao, Kehui Yao, Pratheek Vadla, Praveen Kanumala, Priyank Gupta, Reza Yousefi Maragheh, Sushant Kumar","submitted_at":"2025-06-27T05:45:59Z","abstract_excerpt":"Retrieval-Augmented Generation (RAG) has shown promise in enhancing recommendation systems by incorporating external context into large language model prompts. However, existing RAG-based approaches often rely on static retrieval heuristics and fail to capture nuanced user preferences in dynamic recommendation scenarios. In this work, we introduce ARAG, an Agentic Retrieval-Augmented Generation framework for Personalized Recommendation, which integrates a multi-agent collaboration mechanism into the RAG pipeline. To better understand the long-term and session behavior of the user, ARAG leverag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21931","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/2506.21931/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":"2026-07-05T11:52:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t4iq6O5jkQeloXF8CWsaBwb6tBDbmy8/ksg3veeCpdSkAiFupM+YsOoXToMUFwbbBrj+ZzWHDzXQUdX4tVIOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:34:06.289255Z"},"content_sha256":"50f91a52cfa7bc132fb57c63aa67f3aaf95886b36d3ad8cea304a26373ee4370","schema_version":"1.0","event_id":"sha256:50f91a52cfa7bc132fb57c63aa67f3aaf95886b36d3ad8cea304a26373ee4370"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/bundle.json","state_url":"https://pith.science/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/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":"2026-08-07T07:34:06Z","links":{"resolver":"https://pith.science/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN","bundle":"https://pith.science/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/bundle.json","state":"https://pith.science/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MBWMF4UJHZTZXIXJIM2KHZPEBN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MBWMF4UJHZTZXIXJIM2KHZPEBN","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":"baa9b24a9c7b490caf2fe84d08883d193add7c5e77a357a2303acba6ba4787be","cross_cats_sorted":["cs.AI","cs.CL","cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-27T05:45:59Z","title_canon_sha256":"5204c2c0203d47d962ba990c2e849f844765227b6b5fe8545f92938cb07a9eac"},"schema_version":"1.0","source":{"id":"2506.21931","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21931","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21931v2","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21931","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_12","alias_value":"MBWMF4UJHZTZ","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_16","alias_value":"MBWMF4UJHZTZXIXJ","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_8","alias_value":"MBWMF4UJ","created_at":"2026-07-05T11:52:02Z"}],"graph_snapshots":[{"event_id":"sha256:50f91a52cfa7bc132fb57c63aa67f3aaf95886b36d3ad8cea304a26373ee4370","target":"graph","created_at":"2026-07-05T11:52:02Z","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/2506.21931/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-Augmented Generation (RAG) has shown promise in enhancing recommendation systems by incorporating external context into large language model prompts. However, existing RAG-based approaches often rely on static retrieval heuristics and fail to capture nuanced user preferences in dynamic recommendation scenarios. In this work, we introduce ARAG, an Agentic Retrieval-Augmented Generation framework for Personalized Recommendation, which integrates a multi-agent collaboration mechanism into the RAG pipeline. To better understand the long-term and session behavior of the user, ARAG leverag","authors_text":"Aysenur Inan, Jason Cho, Jianpeng Xu, Kai Zhao, Kehui Yao, Pratheek Vadla, Praveen Kanumala, Priyank Gupta, Reza Yousefi Maragheh, Sushant Kumar","cross_cats":["cs.AI","cs.CL","cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-27T05:45:59Z","title":"ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21931","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:c89c03585d712765437c7f77adecf5da388b9d2db12eb0778cbed2f11130afe3","target":"record","created_at":"2026-07-05T11:52:02Z","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":"baa9b24a9c7b490caf2fe84d08883d193add7c5e77a357a2303acba6ba4787be","cross_cats_sorted":["cs.AI","cs.CL","cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-27T05:45:59Z","title_canon_sha256":"5204c2c0203d47d962ba990c2e849f844765227b6b5fe8545f92938cb07a9eac"},"schema_version":"1.0","source":{"id":"2506.21931","kind":"arxiv","version":2}},"canonical_sha256":"606cc2f2893e679ba2e94334a3e5e40b67be6d7d813b048d12b868bfe218a13a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"606cc2f2893e679ba2e94334a3e5e40b67be6d7d813b048d12b868bfe218a13a","first_computed_at":"2026-07-05T11:52:02.990393Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:52:02.990393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xYDeObbLqz8DsWt2lhNpqx1it3Q/L2e++2MjzYRn7dMXBuNWCGz2hXqGQs/8N7XmOr1ytbFyVKyPTl7KX2yQAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:52:02.990922Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21931","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c89c03585d712765437c7f77adecf5da388b9d2db12eb0778cbed2f11130afe3","sha256:50f91a52cfa7bc132fb57c63aa67f3aaf95886b36d3ad8cea304a26373ee4370"],"state_sha256":"9a78ae67d1f6e9e0c290b625eed4602a05dd02f04c7103d972a7ec9b99d28519"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"opzne1res0Aaj26dlJnPnFgtaxhKthV3HTYS5qDLIID8cVQiRPKtCRX+1Du+kDAqMmpqc4NQ6gpzcNyczX2VDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T07:34:06.293122Z","bundle_sha256":"3d70b0c663d78496c718dc7d6d4707d97636d1a4d0b884e7b9ee9659f1c646a2"}}