{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:QHO5O2TFENICLOIZMXIEGVVXVS","short_pith_number":"pith:QHO5O2TF","canonical_record":{"source":{"id":"2605.24938","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-24T08:36:34Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"71001f98cd08dd064a175f4584faf5a575157ed902876b572c7721f633e55488","abstract_canon_sha256":"29189cedfd83b074f038ccbdccf0982565911afa189d60a8936101b3ca87a7a0"},"schema_version":"1.0"},"canonical_sha256":"81ddd76a65235025b91965d04356b7acad531c007999bd5fb75ad35eb4745e31","source":{"kind":"arxiv","id":"2605.24938","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.24938","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.24938v1","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.24938","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"QHO5O2TFENIC","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_16","alias_value":"QHO5O2TFENICLOIZ","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_8","alias_value":"QHO5O2TF","created_at":"2026-05-26T01:04:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:QHO5O2TFENICLOIZMXIEGVVXVS","target":"record","payload":{"canonical_record":{"source":{"id":"2605.24938","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-24T08:36:34Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"71001f98cd08dd064a175f4584faf5a575157ed902876b572c7721f633e55488","abstract_canon_sha256":"29189cedfd83b074f038ccbdccf0982565911afa189d60a8936101b3ca87a7a0"},"schema_version":"1.0"},"canonical_sha256":"81ddd76a65235025b91965d04356b7acad531c007999bd5fb75ad35eb4745e31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:04:06.699994Z","signature_b64":"nfr9emPVTUnRmX+0OGlMIuxZQ6Na1knd+nKwShae66f6no0YfzoANCTY13dh/OuRcoqp9/fwoaX36J3iksJ8Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"81ddd76a65235025b91965d04356b7acad531c007999bd5fb75ad35eb4745e31","last_reissued_at":"2026-05-26T01:04:06.699205Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:04:06.699205Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.24938","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-26T01:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jgpY1U/8WcKjXRCoEPBU38hUD6frOiUU7vriNrU4YZP2K7VisZt6XfB4r+oZfp8Ws9QTZjXCjyBGAtae0z3VBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T03:16:29.015152Z"},"content_sha256":"5bdcb78cd4cb57492b3617cb7cc9478bb7d4482a82cc2b7cb1a727801a962b06","schema_version":"1.0","event_id":"sha256:5bdcb78cd4cb57492b3617cb7cc9478bb7d4482a82cc2b7cb1a727801a962b06"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:QHO5O2TFENICLOIZMXIEGVVXVS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Your Embedding Model is SMARTer Than You Think","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.IR","authors_text":"Donghyun Kim, Hyun Jung Lee, Jianrui Zhang, Sukanta Ganguly, Tae-Eui Kam, Yong Jae Lee","submitted_at":"2026-05-24T08:36:34Z","abstract_excerpt":"Multimodal retrieval relies heavily on single-vector retrievers, which compress rich, sequential token sequences into one single global representation. While efficient, they discard fine-grained, local evidence critical for dense retrieval tasks. Multi-vector approaches were introduced as a solution, but they strictly require training and many ignore the necessity of a globally summarizing representation. To address this, we introduce SMART, a framework that unlocks the latent multi-vector capabilities of standard single-vector models. We first demonstrate that standard contrastive training on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.24938","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/2605.24938/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":"2026-05-26T01:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U7Isu02FnhcqL5DRvNGzGJstqqZwYv85UF6kaMiVPMghhyz+bvEAunpK/3UL3nIjw4LsUTNKEHg7ylGQoQtoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T03:16:29.016074Z"},"content_sha256":"2fdb9868190203ea0c4602e401f682ab8a5a324380868bb1c23019c9d5165b2b","schema_version":"1.0","event_id":"sha256:2fdb9868190203ea0c4602e401f682ab8a5a324380868bb1c23019c9d5165b2b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QHO5O2TFENICLOIZMXIEGVVXVS/bundle.json","state_url":"https://pith.science/pith/QHO5O2TFENICLOIZMXIEGVVXVS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QHO5O2TFENICLOIZMXIEGVVXVS/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":"2026-05-31T03:16:29Z","links":{"resolver":"https://pith.science/pith/QHO5O2TFENICLOIZMXIEGVVXVS","bundle":"https://pith.science/pith/QHO5O2TFENICLOIZMXIEGVVXVS/bundle.json","state":"https://pith.science/pith/QHO5O2TFENICLOIZMXIEGVVXVS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QHO5O2TFENICLOIZMXIEGVVXVS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QHO5O2TFENICLOIZMXIEGVVXVS","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":"29189cedfd83b074f038ccbdccf0982565911afa189d60a8936101b3ca87a7a0","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-24T08:36:34Z","title_canon_sha256":"71001f98cd08dd064a175f4584faf5a575157ed902876b572c7721f633e55488"},"schema_version":"1.0","source":{"id":"2605.24938","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.24938","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.24938v1","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.24938","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"QHO5O2TFENIC","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_16","alias_value":"QHO5O2TFENICLOIZ","created_at":"2026-05-26T01:04:06Z"},{"alias_kind":"pith_short_8","alias_value":"QHO5O2TF","created_at":"2026-05-26T01:04:06Z"}],"graph_snapshots":[{"event_id":"sha256:2fdb9868190203ea0c4602e401f682ab8a5a324380868bb1c23019c9d5165b2b","target":"graph","created_at":"2026-05-26T01:04:06Z","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/2605.24938/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal retrieval relies heavily on single-vector retrievers, which compress rich, sequential token sequences into one single global representation. While efficient, they discard fine-grained, local evidence critical for dense retrieval tasks. Multi-vector approaches were introduced as a solution, but they strictly require training and many ignore the necessity of a globally summarizing representation. To address this, we introduce SMART, a framework that unlocks the latent multi-vector capabilities of standard single-vector models. We first demonstrate that standard contrastive training on","authors_text":"Donghyun Kim, Hyun Jung Lee, Jianrui Zhang, Sukanta Ganguly, Tae-Eui Kam, Yong Jae Lee","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-24T08:36:34Z","title":"Your Embedding Model is SMARTer Than You Think"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.24938","kind":"arxiv","version":1},"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":"sha256:5bdcb78cd4cb57492b3617cb7cc9478bb7d4482a82cc2b7cb1a727801a962b06","target":"record","created_at":"2026-05-26T01:04:06Z","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":"29189cedfd83b074f038ccbdccf0982565911afa189d60a8936101b3ca87a7a0","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-24T08:36:34Z","title_canon_sha256":"71001f98cd08dd064a175f4584faf5a575157ed902876b572c7721f633e55488"},"schema_version":"1.0","source":{"id":"2605.24938","kind":"arxiv","version":1}},"canonical_sha256":"81ddd76a65235025b91965d04356b7acad531c007999bd5fb75ad35eb4745e31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81ddd76a65235025b91965d04356b7acad531c007999bd5fb75ad35eb4745e31","first_computed_at":"2026-05-26T01:04:06.699205Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:04:06.699205Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nfr9emPVTUnRmX+0OGlMIuxZQ6Na1knd+nKwShae66f6no0YfzoANCTY13dh/OuRcoqp9/fwoaX36J3iksJ8Bg==","signature_status":"signed_v1","signed_at":"2026-05-26T01:04:06.699994Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.24938","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5bdcb78cd4cb57492b3617cb7cc9478bb7d4482a82cc2b7cb1a727801a962b06","sha256:2fdb9868190203ea0c4602e401f682ab8a5a324380868bb1c23019c9d5165b2b"],"state_sha256":"4a2886aa8f2b7c6e955e3975cd349577c8508271dea61a1876489a5c7b79677c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1xNRwV0FrZgtgmhDVgpdiVlKWrfpD98IoKDRW98bQPUf2Ik371oluFFCWwwv/4HYtOvHUIM7AG95HR7huI1zDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T03:16:29.019028Z","bundle_sha256":"9aa8d68c7f1e1a29685a784264653c386f4084ab1e465ebaf3aa4deceab04c01"}}