{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:P4THYW2GJKOKMIVT346FTAT2KS","short_pith_number":"pith:P4THYW2G","canonical_record":{"source":{"id":"2205.10178","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T13:41:12Z","cross_cats_sorted":[],"title_canon_sha256":"8f3cf0239170085bbf780baef02193a6757155e44639a46360d7a01172ed974a","abstract_canon_sha256":"ac5986bf22892dff5c126bcd08501da2ad5a06e712f138814e83888643533c03"},"schema_version":"1.0"},"canonical_sha256":"7f267c5b464a9ca622b3df3c59827a54aedc9b05d8ad07bc1bef65c1b5b2d802","source":{"kind":"arxiv","id":"2205.10178","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.10178","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"arxiv_version","alias_value":"2205.10178v2","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.10178","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_12","alias_value":"P4THYW2GJKOK","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_16","alias_value":"P4THYW2GJKOKMIVT","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_8","alias_value":"P4THYW2G","created_at":"2026-07-05T05:45:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:P4THYW2GJKOKMIVT346FTAT2KS","target":"record","payload":{"canonical_record":{"source":{"id":"2205.10178","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T13:41:12Z","cross_cats_sorted":[],"title_canon_sha256":"8f3cf0239170085bbf780baef02193a6757155e44639a46360d7a01172ed974a","abstract_canon_sha256":"ac5986bf22892dff5c126bcd08501da2ad5a06e712f138814e83888643533c03"},"schema_version":"1.0"},"canonical_sha256":"7f267c5b464a9ca622b3df3c59827a54aedc9b05d8ad07bc1bef65c1b5b2d802","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:45:28.543362Z","signature_b64":"T7tLZhQPAL3dc4TLR+KW8mH86T8/NDQTMsfEky2tWmBJPbGbd2pGEq21niWachhwrCAMv7/MVN80/BeaSiJhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f267c5b464a9ca622b3df3c59827a54aedc9b05d8ad07bc1bef65c1b5b2d802","last_reissued_at":"2026-07-05T05:45:28.542915Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:45:28.542915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.10178","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":"2026-07-05T05:45:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IX6X6q2trvX9FTITV8nOV8NTg4DXwonK5sjfzUaeKYfRT/wmXPHimII+KhybaXTT/Fi9FtuiPx6rorOwTZgDBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T20:12:58.222853Z"},"content_sha256":"9874fb96d414180479aa0bc7b6a8c8169c9eb33ab9d5891adebe0fc698f98fe6","schema_version":"1.0","event_id":"sha256:9874fb96d414180479aa0bc7b6a8c8169c9eb33ab9d5891adebe0fc698f98fe6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:P4THYW2GJKOKMIVT346FTAT2KS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Visually-Augmented Language Modeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Furu Wei, Hao Cheng, Haoyu Song, Jianfeng Gao, Li Dong, Weizhi Wang, XiaoDong Liu, Xifeng Yan","submitted_at":"2022-05-20T13:41:12Z","abstract_excerpt":"Human language is grounded on multimodal knowledge including visual knowledge like colors, sizes, and shapes. However, current large-scale pre-trained language models rely on text-only self-supervised training with massive text data, which precludes them from utilizing relevant visual information when necessary. To address this, we propose a novel pre-training framework, named VaLM, to Visually-augment text tokens with retrieved relevant images for Language Modeling. Specifically, VaLM builds on a novel latent text-image alignment method via an image retrieval module to fetch corresponding ima"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.10178","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/2205.10178/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":"2026-07-05T05:45:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EIlYheFOdpq1tLXH0rvb93CQOlH3jGcf2jppqAABJTreF+bkmx41NczF6S2MHfe6/0hMhIhUg9jzaQYjyi9QDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T20:12:58.223946Z"},"content_sha256":"4f3ba292dbc3b39aa8536e6d90d741ba3b8c2fedfdaf7193631919a2d1a6bee5","schema_version":"1.0","event_id":"sha256:4f3ba292dbc3b39aa8536e6d90d741ba3b8c2fedfdaf7193631919a2d1a6bee5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P4THYW2GJKOKMIVT346FTAT2KS/bundle.json","state_url":"https://pith.science/pith/P4THYW2GJKOKMIVT346FTAT2KS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P4THYW2GJKOKMIVT346FTAT2KS/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":"2026-08-12T20:12:58Z","links":{"resolver":"https://pith.science/pith/P4THYW2GJKOKMIVT346FTAT2KS","bundle":"https://pith.science/pith/P4THYW2GJKOKMIVT346FTAT2KS/bundle.json","state":"https://pith.science/pith/P4THYW2GJKOKMIVT346FTAT2KS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P4THYW2GJKOKMIVT346FTAT2KS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:P4THYW2GJKOKMIVT346FTAT2KS","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":"ac5986bf22892dff5c126bcd08501da2ad5a06e712f138814e83888643533c03","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T13:41:12Z","title_canon_sha256":"8f3cf0239170085bbf780baef02193a6757155e44639a46360d7a01172ed974a"},"schema_version":"1.0","source":{"id":"2205.10178","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.10178","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"arxiv_version","alias_value":"2205.10178v2","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.10178","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_12","alias_value":"P4THYW2GJKOK","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_16","alias_value":"P4THYW2GJKOKMIVT","created_at":"2026-07-05T05:45:28Z"},{"alias_kind":"pith_short_8","alias_value":"P4THYW2G","created_at":"2026-07-05T05:45:28Z"}],"graph_snapshots":[{"event_id":"sha256:4f3ba292dbc3b39aa8536e6d90d741ba3b8c2fedfdaf7193631919a2d1a6bee5","target":"graph","created_at":"2026-07-05T05:45:28Z","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/2205.10178/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Human language is grounded on multimodal knowledge including visual knowledge like colors, sizes, and shapes. However, current large-scale pre-trained language models rely on text-only self-supervised training with massive text data, which precludes them from utilizing relevant visual information when necessary. To address this, we propose a novel pre-training framework, named VaLM, to Visually-augment text tokens with retrieved relevant images for Language Modeling. Specifically, VaLM builds on a novel latent text-image alignment method via an image retrieval module to fetch corresponding ima","authors_text":"Furu Wei, Hao Cheng, Haoyu Song, Jianfeng Gao, Li Dong, Weizhi Wang, XiaoDong Liu, Xifeng Yan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T13:41:12Z","title":"Visually-Augmented Language Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.10178","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":"sha256:9874fb96d414180479aa0bc7b6a8c8169c9eb33ab9d5891adebe0fc698f98fe6","target":"record","created_at":"2026-07-05T05:45:28Z","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":"ac5986bf22892dff5c126bcd08501da2ad5a06e712f138814e83888643533c03","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T13:41:12Z","title_canon_sha256":"8f3cf0239170085bbf780baef02193a6757155e44639a46360d7a01172ed974a"},"schema_version":"1.0","source":{"id":"2205.10178","kind":"arxiv","version":2}},"canonical_sha256":"7f267c5b464a9ca622b3df3c59827a54aedc9b05d8ad07bc1bef65c1b5b2d802","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f267c5b464a9ca622b3df3c59827a54aedc9b05d8ad07bc1bef65c1b5b2d802","first_computed_at":"2026-07-05T05:45:28.542915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:45:28.542915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"T7tLZhQPAL3dc4TLR+KW8mH86T8/NDQTMsfEky2tWmBJPbGbd2pGEq21niWachhwrCAMv7/MVN80/BeaSiJhBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:45:28.543362Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.10178","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9874fb96d414180479aa0bc7b6a8c8169c9eb33ab9d5891adebe0fc698f98fe6","sha256:4f3ba292dbc3b39aa8536e6d90d741ba3b8c2fedfdaf7193631919a2d1a6bee5"],"state_sha256":"712a54762f98851e9eb3e82ad75ac859c4008dd95727f3dd81b84f88c6dfa215"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DHEs1iczpgzZLrVSbJYORbm/HtT2cDIGpVpNNWRaLPL4EC+meu9fUvJdqPbcHR1xelTR//t4MFpntfydl60FDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T20:12:58.235641Z","bundle_sha256":"3a78f1a4018d758ee5f61b1d493d3e485f49dc06b799c29bc1a07b873fc88999"}}