{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GB2ANSU2CQJKTE4MXMNOIOHILM","short_pith_number":"pith:GB2ANSU2","canonical_record":{"source":{"id":"2410.04830","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-07T08:34:18Z","cross_cats_sorted":[],"title_canon_sha256":"9f1598d0b3f5d50a6f4f7ba6c60ab9126ed7a207c3695d90e1911d2f1e860719","abstract_canon_sha256":"091c5ce158783a0a7f6c62f5e38f680edba07f4e5c2420e9e709fbd95b10f37f"},"schema_version":"1.0"},"canonical_sha256":"307406ca9a1412a9938cbb1ae438e85b257b685fc4c1b4e98ded852831ddb9e6","source":{"kind":"arxiv","id":"2410.04830","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04830","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04830v2","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04830","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"GB2ANSU2CQJK","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"GB2ANSU2CQJKTE4M","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"GB2ANSU2","created_at":"2026-07-05T11:09:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GB2ANSU2CQJKTE4MXMNOIOHILM","target":"record","payload":{"canonical_record":{"source":{"id":"2410.04830","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-07T08:34:18Z","cross_cats_sorted":[],"title_canon_sha256":"9f1598d0b3f5d50a6f4f7ba6c60ab9126ed7a207c3695d90e1911d2f1e860719","abstract_canon_sha256":"091c5ce158783a0a7f6c62f5e38f680edba07f4e5c2420e9e709fbd95b10f37f"},"schema_version":"1.0"},"canonical_sha256":"307406ca9a1412a9938cbb1ae438e85b257b685fc4c1b4e98ded852831ddb9e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:01.261808Z","signature_b64":"0kRnRssrmJVtJRUvEThhMxihI5SpfCpzYhcna+44pnoQ17UoRLcPDJwOvIzrCnYm4044IL/mcOGx83jQ3ODrBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"307406ca9a1412a9938cbb1ae438e85b257b685fc4c1b4e98ded852831ddb9e6","last_reissued_at":"2026-07-05T11:09:01.261367Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:01.261367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.04830","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":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3PPDBHarA6hztdV6r4q8mHbCsvYExyxMdFn5xCzKiV04w6/zhz1IVo83RXblZymE/bzhVkhTrq03LsoCoDbVCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:31:31.236480Z"},"content_sha256":"dfc7c1851e859785cda3cddca66aae8f3fc77d17858fbd0890932d3d411dba3e","schema_version":"1.0","event_id":"sha256:dfc7c1851e859785cda3cddca66aae8f3fc77d17858fbd0890932d3d411dba3e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GB2ANSU2CQJKTE4MXMNOIOHILM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Correcting Popularity Bias in Recommender Systems via Item Loss Equalization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Juno Prent, Masoud Mansoury","submitted_at":"2024-10-07T08:34:18Z","abstract_excerpt":"Recommender Systems (RS) often suffer from popularity bias, where a small set of popular items dominate the recommendation results due to their high interaction rates, leaving many less popular items overlooked. This phenomenon disproportionately benefits users with mainstream tastes while neglecting those with niche interests, leading to unfairness among users and exacerbating disparities in recommendation quality across different user groups. In this paper, we propose an in-processing approach to address this issue by intervening in the training process of recommendation models. Drawing insp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04830","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/2410.04830/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":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PYbng7L53jUBJ0SIHWbFXyyl9P+UTepfoIkkN9RkFJ+EEctNdwmKCbKwEDJNw7wixQzTG8vyGnpvtS/jl0x5Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:31:31.237707Z"},"content_sha256":"e692d8b7228157837442a73e92771297edf92250d0cdcd12772e4151e73d3534","schema_version":"1.0","event_id":"sha256:e692d8b7228157837442a73e92771297edf92250d0cdcd12772e4151e73d3534"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/bundle.json","state_url":"https://pith.science/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/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":"2026-08-21T10:31:31Z","links":{"resolver":"https://pith.science/pith/GB2ANSU2CQJKTE4MXMNOIOHILM","bundle":"https://pith.science/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/bundle.json","state":"https://pith.science/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GB2ANSU2CQJKTE4MXMNOIOHILM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GB2ANSU2CQJKTE4MXMNOIOHILM","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":"091c5ce158783a0a7f6c62f5e38f680edba07f4e5c2420e9e709fbd95b10f37f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-07T08:34:18Z","title_canon_sha256":"9f1598d0b3f5d50a6f4f7ba6c60ab9126ed7a207c3695d90e1911d2f1e860719"},"schema_version":"1.0","source":{"id":"2410.04830","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04830","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04830v2","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04830","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"GB2ANSU2CQJK","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"GB2ANSU2CQJKTE4M","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"GB2ANSU2","created_at":"2026-07-05T11:09:01Z"}],"graph_snapshots":[{"event_id":"sha256:e692d8b7228157837442a73e92771297edf92250d0cdcd12772e4151e73d3534","target":"graph","created_at":"2026-07-05T11:09:01Z","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/2410.04830/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recommender Systems (RS) often suffer from popularity bias, where a small set of popular items dominate the recommendation results due to their high interaction rates, leaving many less popular items overlooked. This phenomenon disproportionately benefits users with mainstream tastes while neglecting those with niche interests, leading to unfairness among users and exacerbating disparities in recommendation quality across different user groups. In this paper, we propose an in-processing approach to address this issue by intervening in the training process of recommendation models. Drawing insp","authors_text":"Juno Prent, Masoud Mansoury","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-07T08:34:18Z","title":"Correcting Popularity Bias in Recommender Systems via Item Loss Equalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04830","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:dfc7c1851e859785cda3cddca66aae8f3fc77d17858fbd0890932d3d411dba3e","target":"record","created_at":"2026-07-05T11:09:01Z","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":"091c5ce158783a0a7f6c62f5e38f680edba07f4e5c2420e9e709fbd95b10f37f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-07T08:34:18Z","title_canon_sha256":"9f1598d0b3f5d50a6f4f7ba6c60ab9126ed7a207c3695d90e1911d2f1e860719"},"schema_version":"1.0","source":{"id":"2410.04830","kind":"arxiv","version":2}},"canonical_sha256":"307406ca9a1412a9938cbb1ae438e85b257b685fc4c1b4e98ded852831ddb9e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"307406ca9a1412a9938cbb1ae438e85b257b685fc4c1b4e98ded852831ddb9e6","first_computed_at":"2026-07-05T11:09:01.261367Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:01.261367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0kRnRssrmJVtJRUvEThhMxihI5SpfCpzYhcna+44pnoQ17UoRLcPDJwOvIzrCnYm4044IL/mcOGx83jQ3ODrBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:01.261808Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04830","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dfc7c1851e859785cda3cddca66aae8f3fc77d17858fbd0890932d3d411dba3e","sha256:e692d8b7228157837442a73e92771297edf92250d0cdcd12772e4151e73d3534"],"state_sha256":"15a939de778ff778a77f341f6584a346637be2de83691674dc76872b44c82479"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AKlTZs//QWrUUAOt14xaZFxHVwzU/XL2qeEvbvjbNgm8qmyXLwrJey90UW4sRyShd6Ey2YEIPn9Hkmx/0KiUDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T10:31:31.250024Z","bundle_sha256":"86e6f886d66fe7add761d774f66b63bcebc322bca3fdeb88b959cf8e2a54db2f"}}