{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3OSMRNQI55O3IEUML7EQSIBMKH","short_pith_number":"pith:3OSMRNQI","canonical_record":{"source":{"id":"2504.10921","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-04-15T07:05:22Z","cross_cats_sorted":[],"title_canon_sha256":"4a159527e3daf2799da6e3006bad752e20e351b22ecc1ecc18e542cbfb4f69ba","abstract_canon_sha256":"19ce1a1d7700b71ed0de213f8aaa97827bea366cbbdf52551d87898cac77eff7"},"schema_version":"1.0"},"canonical_sha256":"dba4c8b608ef5db4128c5fc909202c51d55193fa2e953b29d4ccd332c2378be5","source":{"kind":"arxiv","id":"2504.10921","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.10921","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.10921v2","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.10921","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"3OSMRNQI55O3","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"3OSMRNQI55O3IEUM","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"3OSMRNQI","created_at":"2026-07-05T10:53:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3OSMRNQI55O3IEUML7EQSIBMKH","target":"record","payload":{"canonical_record":{"source":{"id":"2504.10921","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-04-15T07:05:22Z","cross_cats_sorted":[],"title_canon_sha256":"4a159527e3daf2799da6e3006bad752e20e351b22ecc1ecc18e542cbfb4f69ba","abstract_canon_sha256":"19ce1a1d7700b71ed0de213f8aaa97827bea366cbbdf52551d87898cac77eff7"},"schema_version":"1.0"},"canonical_sha256":"dba4c8b608ef5db4128c5fc909202c51d55193fa2e953b29d4ccd332c2378be5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:53:54.143845Z","signature_b64":"oabauxO1NvUt1TjdSrxXmvLFb7pTkpbpphMHrwNnhf2GNCa7xCzQetGBAgTpjtE4yO5QiDrrjxjx8qduNUAACA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dba4c8b608ef5db4128c5fc909202c51d55193fa2e953b29d4ccd332c2378be5","last_reissued_at":"2026-07-05T10:53:54.143191Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:53:54.143191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.10921","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":"2026-07-05T10:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x4PGE7ZWNrxjNVZRjpWDKuP/AKMjAd1vSWTj1bIZ+D9FxvSmmCVN8qhIUbKfxJbnN8/BKzHzdU15eYZGdHdDBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T23:14:14.098763Z"},"content_sha256":"b0d60183c27177686e179dafe3fbabc909d830dfbbb48b2666b28033dad8e3b9","schema_version":"1.0","event_id":"sha256:b0d60183c27177686e179dafe3fbabc909d830dfbbb48b2666b28033dad8e3b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3OSMRNQI55O3IEUML7EQSIBMKH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Guoqing Wang, Jie Zou, Weikang Guo, Xing Xu, Yang Yang, Yibiao Wei","submitted_at":"2025-04-15T07:05:22Z","abstract_excerpt":"Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by interacting with users through conversations. Most existing studies of CRS focus on extracting user preferences from conversational contexts. However, due to the short and sparse nature of conversational contexts, it is difficult to fully capture user preferences by conversational contexts only. We argue that multi-modal semantic information can enrich user preference expressions from diverse dimensions (e.g., a user preference for a certain movie may stem from its magnificent visual effects and compelling"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.10921","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/2504.10921/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":"2026-07-05T10:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nc0iLxMp93bbT1WNdtOZ4z8lOC8ZZkb61HZaRuH7F4f9s9S1/ZFzS9s5NCOCRERY6GGcfaYLxvxRsDwy6RFGDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T23:14:14.099286Z"},"content_sha256":"c3c9d9055a548cb34c97574f499c96a61f1c79eab910e54fa76073a6014d4cac","schema_version":"1.0","event_id":"sha256:c3c9d9055a548cb34c97574f499c96a61f1c79eab910e54fa76073a6014d4cac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3OSMRNQI55O3IEUML7EQSIBMKH/bundle.json","state_url":"https://pith.science/pith/3OSMRNQI55O3IEUML7EQSIBMKH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3OSMRNQI55O3IEUML7EQSIBMKH/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":"2026-08-19T23:14:14Z","links":{"resolver":"https://pith.science/pith/3OSMRNQI55O3IEUML7EQSIBMKH","bundle":"https://pith.science/pith/3OSMRNQI55O3IEUML7EQSIBMKH/bundle.json","state":"https://pith.science/pith/3OSMRNQI55O3IEUML7EQSIBMKH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3OSMRNQI55O3IEUML7EQSIBMKH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3OSMRNQI55O3IEUML7EQSIBMKH","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":"19ce1a1d7700b71ed0de213f8aaa97827bea366cbbdf52551d87898cac77eff7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-04-15T07:05:22Z","title_canon_sha256":"4a159527e3daf2799da6e3006bad752e20e351b22ecc1ecc18e542cbfb4f69ba"},"schema_version":"1.0","source":{"id":"2504.10921","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.10921","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.10921v2","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.10921","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"3OSMRNQI55O3","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"3OSMRNQI55O3IEUM","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"3OSMRNQI","created_at":"2026-07-05T10:53:54Z"}],"graph_snapshots":[{"event_id":"sha256:c3c9d9055a548cb34c97574f499c96a61f1c79eab910e54fa76073a6014d4cac","target":"graph","created_at":"2026-07-05T10:53:54Z","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/2504.10921/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by interacting with users through conversations. Most existing studies of CRS focus on extracting user preferences from conversational contexts. However, due to the short and sparse nature of conversational contexts, it is difficult to fully capture user preferences by conversational contexts only. We argue that multi-modal semantic information can enrich user preference expressions from diverse dimensions (e.g., a user preference for a certain movie may stem from its magnificent visual effects and compelling","authors_text":"Guoqing Wang, Jie Zou, Weikang Guo, Xing Xu, Yang Yang, Yibiao Wei","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-04-15T07:05:22Z","title":"MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.10921","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:b0d60183c27177686e179dafe3fbabc909d830dfbbb48b2666b28033dad8e3b9","target":"record","created_at":"2026-07-05T10:53:54Z","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":"19ce1a1d7700b71ed0de213f8aaa97827bea366cbbdf52551d87898cac77eff7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-04-15T07:05:22Z","title_canon_sha256":"4a159527e3daf2799da6e3006bad752e20e351b22ecc1ecc18e542cbfb4f69ba"},"schema_version":"1.0","source":{"id":"2504.10921","kind":"arxiv","version":2}},"canonical_sha256":"dba4c8b608ef5db4128c5fc909202c51d55193fa2e953b29d4ccd332c2378be5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dba4c8b608ef5db4128c5fc909202c51d55193fa2e953b29d4ccd332c2378be5","first_computed_at":"2026-07-05T10:53:54.143191Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:54.143191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oabauxO1NvUt1TjdSrxXmvLFb7pTkpbpphMHrwNnhf2GNCa7xCzQetGBAgTpjtE4yO5QiDrrjxjx8qduNUAACA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:54.143845Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.10921","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0d60183c27177686e179dafe3fbabc909d830dfbbb48b2666b28033dad8e3b9","sha256:c3c9d9055a548cb34c97574f499c96a61f1c79eab910e54fa76073a6014d4cac"],"state_sha256":"8553a7c9be943ff71cf42aaed6ce50ae7467006717b43f7cae281b7c91754629"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"An29QaltrhyVzzDyKjzClPROce/zzNaIhpaHK8BNBD7iO6CYkAtY/OAS0FEIXzHq9lX34HJZ/KLk7y9phWKYAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T23:14:14.104667Z","bundle_sha256":"5d149a607baa041d39535d70d363eac398bef7ffab2b30ffc78a9b9c4ec104bf"}}