{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2ZMXSUR5EKS7J3TYY56S5HWMHI","short_pith_number":"pith:2ZMXSUR5","canonical_record":{"source":{"id":"2502.20499","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-27T20:14:01Z","cross_cats_sorted":[],"title_canon_sha256":"904516feca285ad60b040de67d269d5a4e7ce50399eebc86acda090131e7bda5","abstract_canon_sha256":"dfd65a5df3b65b89714c26b2b789ed95c43cfb7079fc6530102990de15f9053a"},"schema_version":"1.0"},"canonical_sha256":"d65979523d22a5f4ee78c77d2e9ecc3a1677a062765562cea22529e912257b55","source":{"kind":"arxiv","id":"2502.20499","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.20499","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"arxiv_version","alias_value":"2502.20499v3","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.20499","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_12","alias_value":"2ZMXSUR5EKS7","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_16","alias_value":"2ZMXSUR5EKS7J3TY","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_8","alias_value":"2ZMXSUR5","created_at":"2026-07-05T11:23:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2ZMXSUR5EKS7J3TYY56S5HWMHI","target":"record","payload":{"canonical_record":{"source":{"id":"2502.20499","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-27T20:14:01Z","cross_cats_sorted":[],"title_canon_sha256":"904516feca285ad60b040de67d269d5a4e7ce50399eebc86acda090131e7bda5","abstract_canon_sha256":"dfd65a5df3b65b89714c26b2b789ed95c43cfb7079fc6530102990de15f9053a"},"schema_version":"1.0"},"canonical_sha256":"d65979523d22a5f4ee78c77d2e9ecc3a1677a062765562cea22529e912257b55","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:23:23.726590Z","signature_b64":"ktdco5qpyG1gvebA9gi8YbSNYAisjs4+F7xIcVcSIT5FhkXtuwJL2dLqNpDCJk1zXla49jEV4A5vM35Axi3UBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d65979523d22a5f4ee78c77d2e9ecc3a1677a062765562cea22529e912257b55","last_reissued_at":"2026-07-05T11:23:23.726023Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:23:23.726023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.20499","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:23:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ee3/fcFjpRsLjrPGEk2aCO2YpGxuWBqOZ1fhZCVUoCX2vQs6JK34/npkT5c6lLBXCXRAF8s6OQc6oP0+uJACCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:34:49.515060Z"},"content_sha256":"84255c1e9fbf09f0e294b8c063f24a2dcfa41f3531bb47a7adb80df5c53cb9d0","schema_version":"1.0","event_id":"sha256:84255c1e9fbf09f0e294b8c063f24a2dcfa41f3531bb47a7adb80df5c53cb9d0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2ZMXSUR5EKS7J3TYY56S5HWMHI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data Distributional Properties As Inductive Bias for Systematic Generalization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alain Raymond-Saez, Alvaro Soto, Cristian B. Calderon, Daniel Florea, Felipe del Rio, Julio Hurtado, Rodrigo Toro Icarte","submitted_at":"2025-02-27T20:14:01Z","abstract_excerpt":"Deep neural networks (DNNs) struggle at systematic generalization (SG). Several studies have evaluated the possibility to promote SG through the proposal of novel architectures, loss functions or training methodologies. Few studies, however, have focused on the role of training data properties in promoting SG. In this work, we investigate the impact of certain data distributional properties, as inductive biases for the SG ability of a multi-modal language model. To this end, we study three different properties. First, data diversity, instantiated as an increase in the possible values a latent "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.20499","kind":"arxiv","version":3},"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/2502.20499/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":"2026-07-05T11:23:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IqXuVm3LSM1d+GcFB12nLTcMm38u2k6HWTtaW73obZpa/Pi74LJe7G7iZIfzOIWHEcyLxVm4czEy4BUaJvs5DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:34:49.515731Z"},"content_sha256":"06187b6d29f4cbdaae1781c20879064ac7e03c31205f17eda45d688a147e1488","schema_version":"1.0","event_id":"sha256:06187b6d29f4cbdaae1781c20879064ac7e03c31205f17eda45d688a147e1488"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/bundle.json","state_url":"https://pith.science/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/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":"2026-08-05T00:34:49Z","links":{"resolver":"https://pith.science/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI","bundle":"https://pith.science/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/bundle.json","state":"https://pith.science/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2ZMXSUR5EKS7J3TYY56S5HWMHI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2ZMXSUR5EKS7J3TYY56S5HWMHI","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":"dfd65a5df3b65b89714c26b2b789ed95c43cfb7079fc6530102990de15f9053a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-27T20:14:01Z","title_canon_sha256":"904516feca285ad60b040de67d269d5a4e7ce50399eebc86acda090131e7bda5"},"schema_version":"1.0","source":{"id":"2502.20499","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.20499","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"arxiv_version","alias_value":"2502.20499v3","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.20499","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_12","alias_value":"2ZMXSUR5EKS7","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_16","alias_value":"2ZMXSUR5EKS7J3TY","created_at":"2026-07-05T11:23:23Z"},{"alias_kind":"pith_short_8","alias_value":"2ZMXSUR5","created_at":"2026-07-05T11:23:23Z"}],"graph_snapshots":[{"event_id":"sha256:06187b6d29f4cbdaae1781c20879064ac7e03c31205f17eda45d688a147e1488","target":"graph","created_at":"2026-07-05T11:23:23Z","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/2502.20499/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural networks (DNNs) struggle at systematic generalization (SG). Several studies have evaluated the possibility to promote SG through the proposal of novel architectures, loss functions or training methodologies. Few studies, however, have focused on the role of training data properties in promoting SG. In this work, we investigate the impact of certain data distributional properties, as inductive biases for the SG ability of a multi-modal language model. To this end, we study three different properties. First, data diversity, instantiated as an increase in the possible values a latent ","authors_text":"Alain Raymond-Saez, Alvaro Soto, Cristian B. Calderon, Daniel Florea, Felipe del Rio, Julio Hurtado, Rodrigo Toro Icarte","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-27T20:14:01Z","title":"Data Distributional Properties As Inductive Bias for Systematic Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.20499","kind":"arxiv","version":3},"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":"sha256:84255c1e9fbf09f0e294b8c063f24a2dcfa41f3531bb47a7adb80df5c53cb9d0","target":"record","created_at":"2026-07-05T11:23:23Z","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":"dfd65a5df3b65b89714c26b2b789ed95c43cfb7079fc6530102990de15f9053a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-27T20:14:01Z","title_canon_sha256":"904516feca285ad60b040de67d269d5a4e7ce50399eebc86acda090131e7bda5"},"schema_version":"1.0","source":{"id":"2502.20499","kind":"arxiv","version":3}},"canonical_sha256":"d65979523d22a5f4ee78c77d2e9ecc3a1677a062765562cea22529e912257b55","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d65979523d22a5f4ee78c77d2e9ecc3a1677a062765562cea22529e912257b55","first_computed_at":"2026-07-05T11:23:23.726023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:23:23.726023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ktdco5qpyG1gvebA9gi8YbSNYAisjs4+F7xIcVcSIT5FhkXtuwJL2dLqNpDCJk1zXla49jEV4A5vM35Axi3UBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:23:23.726590Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.20499","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:84255c1e9fbf09f0e294b8c063f24a2dcfa41f3531bb47a7adb80df5c53cb9d0","sha256:06187b6d29f4cbdaae1781c20879064ac7e03c31205f17eda45d688a147e1488"],"state_sha256":"d4a01c480e8e8ece5242258148398a8603ceffd61cdc1281140656beab3d4277"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4bAHbinujoi2wZItn8FGDZLzhe4S8Jhbe0aEtBXgU7GM0nCKBhtevkYZVhufKj+ZRx0Fj8zPfHcoQuy78yXzDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T00:34:49.522373Z","bundle_sha256":"abcee75530c26f8bba049d0d9503f1f4e6a529981a0e0b29c7fd08cf05d1bf91"}}