{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:R6PTL7PE7HTIQEWHFW3JWJ75BA","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":"76cfd18fb03f11fa38e005a6b8b0e2f45fe7096343f54397831a647293d5a033","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-07-16T13:30:14Z","title_canon_sha256":"1658cff716fa0a64b4884178db70a2cb756cc195ae4ae53d30e283e61c9eb513"},"schema_version":"1.0","source":{"id":"2407.11712","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.11712","created_at":"2026-07-05T10:08:19Z"},{"alias_kind":"arxiv_version","alias_value":"2407.11712v4","created_at":"2026-07-05T10:08:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11712","created_at":"2026-07-05T10:08:19Z"},{"alias_kind":"pith_short_12","alias_value":"R6PTL7PE7HTI","created_at":"2026-07-05T10:08:19Z"},{"alias_kind":"pith_short_16","alias_value":"R6PTL7PE7HTIQEWH","created_at":"2026-07-05T10:08:19Z"},{"alias_kind":"pith_short_8","alias_value":"R6PTL7PE","created_at":"2026-07-05T10:08:19Z"}],"graph_snapshots":[{"event_id":"sha256:b6ffbe84b8af6e677920f7067d47d300752f73e1bb845eba9264d01decbaa0d5","target":"graph","created_at":"2026-07-05T10:08:19Z","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/2407.11712/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in product bundling have leveraged multimodal information through sophisticated encoders, but remain constrained by limited semantic understanding and a narrow scope of knowledge. Therefore, some attempts employ In-context Learning (ICL) to explore the potential of large language models (LLMs) for their extensive knowledge and complex reasoning abilities. However, these efforts are inadequate in understanding mulitmodal data and exploiting LLMs' knowledge for product bundling. To bridge the gap, we introduce Bundle-MLLM, a novel framework that fine-tunes LLMs through a hybrid i","authors_text":"Jie Wu, Tat-Seng Chua, Xiaohao Liu, Yinwei Wei, Yunshan Ma, Zhulin Tao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-07-16T13:30:14Z","title":"Fine-tuning Multimodal Large Language Models for Product Bundling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11712","kind":"arxiv","version":4},"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":"sha256:27c973ce58a3b9dc0f11cc11cd156fdd301f4e214fba2fafed9fcb01f1724b6e","target":"record","created_at":"2026-07-05T10:08:19Z","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":"76cfd18fb03f11fa38e005a6b8b0e2f45fe7096343f54397831a647293d5a033","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-07-16T13:30:14Z","title_canon_sha256":"1658cff716fa0a64b4884178db70a2cb756cc195ae4ae53d30e283e61c9eb513"},"schema_version":"1.0","source":{"id":"2407.11712","kind":"arxiv","version":4}},"canonical_sha256":"8f9f35fde4f9e68812c72db69b27fd0809aa50fc4247d82fa3cd42786d21df9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f9f35fde4f9e68812c72db69b27fd0809aa50fc4247d82fa3cd42786d21df9e","first_computed_at":"2026-07-05T10:08:19.328559Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:08:19.328559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VUrhzXB71yM95IPd5LrhGnw4xcyIiqULIvAbt9KpxQIHX+ZH1VWwx892gF+t70g1bOxolCuPTSJutIsJ2NEmCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:08:19.329019Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.11712","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:27c973ce58a3b9dc0f11cc11cd156fdd301f4e214fba2fafed9fcb01f1724b6e","sha256:b6ffbe84b8af6e677920f7067d47d300752f73e1bb845eba9264d01decbaa0d5"],"state_sha256":"09adabb3f130c566cdafa0a86b59d23f55ec45fbf140a1be0bf87ad8546af4fe"}