{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LDU26XTZF3UUEVRQAEVPPNLY4F","short_pith_number":"pith:LDU26XTZ","canonical_record":{"source":{"id":"2507.11866","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-07-16T03:26:24Z","cross_cats_sorted":[],"title_canon_sha256":"41642fbd4cbd7d7f73d9eb8db708ea77fc649aa0b0cda646a51099a94471456c","abstract_canon_sha256":"50fe5475b7b4344ccdec822c76309da7a6fdee8885cf6eb13ee92afdfb16e596"},"schema_version":"1.0"},"canonical_sha256":"58e9af5e792ee9425630012af7b578e16bb83ccf134ff7e38d79fc1abfb342e3","source":{"kind":"arxiv","id":"2507.11866","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.11866","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"arxiv_version","alias_value":"2507.11866v1","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11866","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_12","alias_value":"LDU26XTZF3UU","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_16","alias_value":"LDU26XTZF3UUEVRQ","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_8","alias_value":"LDU26XTZ","created_at":"2026-07-05T11:37:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LDU26XTZF3UUEVRQAEVPPNLY4F","target":"record","payload":{"canonical_record":{"source":{"id":"2507.11866","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-07-16T03:26:24Z","cross_cats_sorted":[],"title_canon_sha256":"41642fbd4cbd7d7f73d9eb8db708ea77fc649aa0b0cda646a51099a94471456c","abstract_canon_sha256":"50fe5475b7b4344ccdec822c76309da7a6fdee8885cf6eb13ee92afdfb16e596"},"schema_version":"1.0"},"canonical_sha256":"58e9af5e792ee9425630012af7b578e16bb83ccf134ff7e38d79fc1abfb342e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:37:52.366147Z","signature_b64":"mU2A43wfvJWNkWIo2sQ48IAkFwtBqhT3UMcXlHa6EMkgLYiIXsaZ62+mUg/yn5dth9QDRWeNQ3QZNTjs3Ss5Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"58e9af5e792ee9425630012af7b578e16bb83ccf134ff7e38d79fc1abfb342e3","last_reissued_at":"2026-07-05T11:37:52.365547Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:37:52.365547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.11866","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":"2026-07-05T11:37:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"78E724tIvZzykZXM93eroVTO0wXKN9NezvRsw0+lDNU0MWg6ad6v93FFm5BCPVKefxyKoRNcQP29jAbqZhaxBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:55:41.706034Z"},"content_sha256":"6bb30e8ed716d0dd6947e6bf606bb3272297992c3bd5cc72247dd25c055e574f","schema_version":"1.0","event_id":"sha256:6bb30e8ed716d0dd6947e6bf606bb3272297992c3bd5cc72247dd25c055e574f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LDU26XTZF3UUEVRQAEVPPNLY4F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Similarity-Guided Diffusion for Contrastive Sequential Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Donghyeon Park, Jinkyeong Choi, Yejin Noh","submitted_at":"2025-07-16T03:26:24Z","abstract_excerpt":"In sequential recommendation systems, data augmentation and contrastive learning techniques have recently been introduced using diffusion models to achieve robust representation learning. However, most of the existing approaches use random augmentation, which risk damaging the contextual information of the original sequence. Accordingly, we propose a Similarity-Guided Diffusion for Contrastive Sequential Recommendation. Our method leverages the similarity between item embedding vectors to generate semantically consistent noise. Moreover, we utilize high confidence score in the denoising proces"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11866","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/2507.11866/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":"2026-07-05T11:37:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZYENmDp6hmomLHDWKaLb6B+FhjevVYJavj2CUO/fMHOX88ngzg22p2pv3iImrpIEORaBNxHg5pwPmBVUMhidDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:55:41.706970Z"},"content_sha256":"553f0d2a2c101b633bb694b9df0736363a7f29c42ebf25414668917212216f1e","schema_version":"1.0","event_id":"sha256:553f0d2a2c101b633bb694b9df0736363a7f29c42ebf25414668917212216f1e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/bundle.json","state_url":"https://pith.science/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/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":"2026-08-08T12:55:41Z","links":{"resolver":"https://pith.science/pith/LDU26XTZF3UUEVRQAEVPPNLY4F","bundle":"https://pith.science/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/bundle.json","state":"https://pith.science/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LDU26XTZF3UUEVRQAEVPPNLY4F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LDU26XTZF3UUEVRQAEVPPNLY4F","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":"50fe5475b7b4344ccdec822c76309da7a6fdee8885cf6eb13ee92afdfb16e596","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-07-16T03:26:24Z","title_canon_sha256":"41642fbd4cbd7d7f73d9eb8db708ea77fc649aa0b0cda646a51099a94471456c"},"schema_version":"1.0","source":{"id":"2507.11866","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.11866","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"arxiv_version","alias_value":"2507.11866v1","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11866","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_12","alias_value":"LDU26XTZF3UU","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_16","alias_value":"LDU26XTZF3UUEVRQ","created_at":"2026-07-05T11:37:52Z"},{"alias_kind":"pith_short_8","alias_value":"LDU26XTZ","created_at":"2026-07-05T11:37:52Z"}],"graph_snapshots":[{"event_id":"sha256:553f0d2a2c101b633bb694b9df0736363a7f29c42ebf25414668917212216f1e","target":"graph","created_at":"2026-07-05T11:37:52Z","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/2507.11866/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In sequential recommendation systems, data augmentation and contrastive learning techniques have recently been introduced using diffusion models to achieve robust representation learning. However, most of the existing approaches use random augmentation, which risk damaging the contextual information of the original sequence. Accordingly, we propose a Similarity-Guided Diffusion for Contrastive Sequential Recommendation. Our method leverages the similarity between item embedding vectors to generate semantically consistent noise. Moreover, we utilize high confidence score in the denoising proces","authors_text":"Donghyeon Park, Jinkyeong Choi, Yejin Noh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-07-16T03:26:24Z","title":"Similarity-Guided Diffusion for Contrastive Sequential Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11866","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":"sha256:6bb30e8ed716d0dd6947e6bf606bb3272297992c3bd5cc72247dd25c055e574f","target":"record","created_at":"2026-07-05T11:37:52Z","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":"50fe5475b7b4344ccdec822c76309da7a6fdee8885cf6eb13ee92afdfb16e596","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-07-16T03:26:24Z","title_canon_sha256":"41642fbd4cbd7d7f73d9eb8db708ea77fc649aa0b0cda646a51099a94471456c"},"schema_version":"1.0","source":{"id":"2507.11866","kind":"arxiv","version":1}},"canonical_sha256":"58e9af5e792ee9425630012af7b578e16bb83ccf134ff7e38d79fc1abfb342e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58e9af5e792ee9425630012af7b578e16bb83ccf134ff7e38d79fc1abfb342e3","first_computed_at":"2026-07-05T11:37:52.365547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:37:52.365547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mU2A43wfvJWNkWIo2sQ48IAkFwtBqhT3UMcXlHa6EMkgLYiIXsaZ62+mUg/yn5dth9QDRWeNQ3QZNTjs3Ss5Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:37:52.366147Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.11866","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6bb30e8ed716d0dd6947e6bf606bb3272297992c3bd5cc72247dd25c055e574f","sha256:553f0d2a2c101b633bb694b9df0736363a7f29c42ebf25414668917212216f1e"],"state_sha256":"f800a7d3b3bcbdd942807fd5c135981d7ac67c0ab83a1d9b87059bd61cb05378"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bX2qme8w/8fGNEaykVY55I5SrSjkwdvX0R+8QT7N4rv7ZXE/LYpZ3NeSsuofhVaBv/RkDbkUpGBFaRwimW4fCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T12:55:41.712823Z","bundle_sha256":"b8c0e1c059390085a3dc727f4b62857a3d2202fa20c7395193621624c082eb48"}}