{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:N3OSEZLIAO4SD6F5SKXFFZOG4L","short_pith_number":"pith:N3OSEZLI","canonical_record":{"source":{"id":"2206.09059","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-18T00:16:37Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"0e897875bb3398d065d041ae84699e5f4cc515261215c15742cfca4124c438ea","abstract_canon_sha256":"4eb26e6975a083b444dbdd2366e10c7c958acf74c4c8f9204ab55a5516f45244"},"schema_version":"1.0"},"canonical_sha256":"6edd22656803b921f8bd92ae52e5c6e2e88ab482ddd9633630abe45ddd122099","source":{"kind":"arxiv","id":"2206.09059","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.09059","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"arxiv_version","alias_value":"2206.09059v2","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.09059","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_12","alias_value":"N3OSEZLIAO4S","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_16","alias_value":"N3OSEZLIAO4SD6F5","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_8","alias_value":"N3OSEZLI","created_at":"2026-07-05T05:19:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:N3OSEZLIAO4SD6F5SKXFFZOG4L","target":"record","payload":{"canonical_record":{"source":{"id":"2206.09059","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-18T00:16:37Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"0e897875bb3398d065d041ae84699e5f4cc515261215c15742cfca4124c438ea","abstract_canon_sha256":"4eb26e6975a083b444dbdd2366e10c7c958acf74c4c8f9204ab55a5516f45244"},"schema_version":"1.0"},"canonical_sha256":"6edd22656803b921f8bd92ae52e5c6e2e88ab482ddd9633630abe45ddd122099","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:19:16.955175Z","signature_b64":"0s7BvB/hbzTny7faxaVzmt/tAna5D35Ms/SL9jXvbzuEFZ9M/fzOAqvN2TFiaJsmQFECyj6+9dJkgsAvSZtdBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6edd22656803b921f8bd92ae52e5c6e2e88ab482ddd9633630abe45ddd122099","last_reissued_at":"2026-07-05T05:19:16.954757Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:19:16.954757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.09059","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":"2026-07-05T05:19:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YU3NHmTowgv+E6B6OiIup+m6HiYRo8p0FXOyKQMGBF6VgXTTZ2QIzLPjNKiljtE68U5gK4V2E5jsc5CZgDCWBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T15:32:28.904324Z"},"content_sha256":"d925660dab1afa9af9c386acbc6e96a994ff509b97bb07b1e3398005c54e5eb9","schema_version":"1.0","event_id":"sha256:d925660dab1afa9af9c386acbc6e96a994ff509b97bb07b1e3398005c54e5eb9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:N3OSEZLIAO4SD6F5SKXFFZOG4L","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"cs.CL","authors_text":"Georgios Chochlakis, Jesse Thomason, Leticia Leonor Pinto Alva, Mohammad Rostami, Tejas Srinivasan, Ting-Yun Chang","submitted_at":"2022-06-18T00:16:37Z","abstract_excerpt":"Current state-of-the-art vision-and-language models are evaluated on tasks either individually or in a multi-task setting, overlooking the challenges of continually learning (CL) tasks as they arrive. Existing CL benchmarks have facilitated research on task adaptation and mitigating \"catastrophic forgetting\", but are limited to vision-only and language-only tasks. We present CLiMB, a benchmark to study the challenge of learning multimodal tasks in a CL setting, and to systematically evaluate how upstream continual learning can rapidly generalize to new multimodal and unimodal tasks. CLiMB incl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.09059","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/2206.09059/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":"2026-07-05T05:19:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q2ouEH5VxXqIX6bVN5j65qqjd48x7VFktBRxa9PC0NHXhsi4JZSV6IFC5pn0rJpnBFmAPIFYjkeZiMFjojCKDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T15:32:28.905228Z"},"content_sha256":"29ab398a26680237743de8a205d3242385258cbfc8a558f68860b04dbf89a4b4","schema_version":"1.0","event_id":"sha256:29ab398a26680237743de8a205d3242385258cbfc8a558f68860b04dbf89a4b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/bundle.json","state_url":"https://pith.science/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/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":"2026-08-15T15:32:28Z","links":{"resolver":"https://pith.science/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L","bundle":"https://pith.science/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/bundle.json","state":"https://pith.science/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N3OSEZLIAO4SD6F5SKXFFZOG4L/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:N3OSEZLIAO4SD6F5SKXFFZOG4L","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":"4eb26e6975a083b444dbdd2366e10c7c958acf74c4c8f9204ab55a5516f45244","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-18T00:16:37Z","title_canon_sha256":"0e897875bb3398d065d041ae84699e5f4cc515261215c15742cfca4124c438ea"},"schema_version":"1.0","source":{"id":"2206.09059","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.09059","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"arxiv_version","alias_value":"2206.09059v2","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.09059","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_12","alias_value":"N3OSEZLIAO4S","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_16","alias_value":"N3OSEZLIAO4SD6F5","created_at":"2026-07-05T05:19:16Z"},{"alias_kind":"pith_short_8","alias_value":"N3OSEZLI","created_at":"2026-07-05T05:19:16Z"}],"graph_snapshots":[{"event_id":"sha256:29ab398a26680237743de8a205d3242385258cbfc8a558f68860b04dbf89a4b4","target":"graph","created_at":"2026-07-05T05:19:16Z","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/2206.09059/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current state-of-the-art vision-and-language models are evaluated on tasks either individually or in a multi-task setting, overlooking the challenges of continually learning (CL) tasks as they arrive. Existing CL benchmarks have facilitated research on task adaptation and mitigating \"catastrophic forgetting\", but are limited to vision-only and language-only tasks. We present CLiMB, a benchmark to study the challenge of learning multimodal tasks in a CL setting, and to systematically evaluate how upstream continual learning can rapidly generalize to new multimodal and unimodal tasks. CLiMB incl","authors_text":"Georgios Chochlakis, Jesse Thomason, Leticia Leonor Pinto Alva, Mohammad Rostami, Tejas Srinivasan, Ting-Yun Chang","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-18T00:16:37Z","title":"CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.09059","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:d925660dab1afa9af9c386acbc6e96a994ff509b97bb07b1e3398005c54e5eb9","target":"record","created_at":"2026-07-05T05:19:16Z","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":"4eb26e6975a083b444dbdd2366e10c7c958acf74c4c8f9204ab55a5516f45244","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-18T00:16:37Z","title_canon_sha256":"0e897875bb3398d065d041ae84699e5f4cc515261215c15742cfca4124c438ea"},"schema_version":"1.0","source":{"id":"2206.09059","kind":"arxiv","version":2}},"canonical_sha256":"6edd22656803b921f8bd92ae52e5c6e2e88ab482ddd9633630abe45ddd122099","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6edd22656803b921f8bd92ae52e5c6e2e88ab482ddd9633630abe45ddd122099","first_computed_at":"2026-07-05T05:19:16.954757Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:19:16.954757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0s7BvB/hbzTny7faxaVzmt/tAna5D35Ms/SL9jXvbzuEFZ9M/fzOAqvN2TFiaJsmQFECyj6+9dJkgsAvSZtdBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:19:16.955175Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.09059","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d925660dab1afa9af9c386acbc6e96a994ff509b97bb07b1e3398005c54e5eb9","sha256:29ab398a26680237743de8a205d3242385258cbfc8a558f68860b04dbf89a4b4"],"state_sha256":"0ff1f311e282bb68604611af86a9027a4ec172a7db4ef00a7a247106250b3c62"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H+ug4UuglzFznuWth63G+Q8hJoa4zQIuzkEe2cbzPLHeCmS/oe79mvM9dSuqfYeiPQBwL2x5Gf1I2Hp+IOOFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T15:32:28.913073Z","bundle_sha256":"8b73a3a7a465375654baf3f08795f191dac36c9505f7f2a7e7a742a0909c3db6"}}