{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:MNNWJO3YLRMPWVA5EX2ADTZMPM","short_pith_number":"pith:MNNWJO3Y","canonical_record":{"source":{"id":"2005.00247","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-01T07:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"279bbd39113cd89ab11478010ad7f817bb8ec0da24e0589af13ce50cea53c8db","abstract_canon_sha256":"2c69db1deeb4f88e9e1bd03163773c56d0efe9609585c8178ea56d44e1ef2535"},"schema_version":"1.0"},"canonical_sha256":"635b64bb785c58fb541d25f401cf2c7b27bee3346cf181ca51c98f17973019fb","source":{"kind":"arxiv","id":"2005.00247","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.00247","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"arxiv_version","alias_value":"2005.00247v3","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.00247","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_12","alias_value":"MNNWJO3YLRMP","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_16","alias_value":"MNNWJO3YLRMPWVA5","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_8","alias_value":"MNNWJO3Y","created_at":"2026-07-05T02:09:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:MNNWJO3YLRMPWVA5EX2ADTZMPM","target":"record","payload":{"canonical_record":{"source":{"id":"2005.00247","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-01T07:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"279bbd39113cd89ab11478010ad7f817bb8ec0da24e0589af13ce50cea53c8db","abstract_canon_sha256":"2c69db1deeb4f88e9e1bd03163773c56d0efe9609585c8178ea56d44e1ef2535"},"schema_version":"1.0"},"canonical_sha256":"635b64bb785c58fb541d25f401cf2c7b27bee3346cf181ca51c98f17973019fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:09:39.147704Z","signature_b64":"8aQWHYeDh/07wd9+tJ6BvkVAmqIv3oZjWEXGpiepGWW0DZUuutZ4XaD8ihbJ+6lYE+hqA+Lg1RCgRVFSg0VxDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"635b64bb785c58fb541d25f401cf2c7b27bee3346cf181ca51c98f17973019fb","last_reissued_at":"2026-07-05T02:09:39.147362Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:09:39.147362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.00247","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":"2026-07-05T02:09:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HjVTMAhuAsa3wd3hhCvY1/W3AmfQbxGwRL5DHDBYGLXA2OoIaGbijHVbIVMw8djtB9Q2KWnr2L0yd5ggStnXDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:23:28.774883Z"},"content_sha256":"bfe78a0808f00512ee26d427877bbd6c4cdb35843e9dca2427d6ec46c756ed78","schema_version":"1.0","event_id":"sha256:bfe78a0808f00512ee26d427877bbd6c4cdb35843e9dca2427d6ec46c756ed78"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:MNNWJO3YLRMPWVA5EX2ADTZMPM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AdapterFusion: Non-Destructive Task Composition for Transfer Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Aishwarya Kamath, Andreas R\\\"uckl\\'e, Iryna Gurevych, Jonas Pfeiffer, Kyunghyun Cho","submitted_at":"2020-05-01T07:03:42Z","abstract_excerpt":"Sequential fine-tuning and multi-task learning are methods aiming to incorporate knowledge from multiple tasks; however, they suffer from catastrophic forgetting and difficulties in dataset balancing. To address these shortcomings, we propose AdapterFusion, a new two stage learning algorithm that leverages knowledge from multiple tasks. First, in the knowledge extraction stage we learn task specific parameters called adapters, that encapsulate the task-specific information. We then combine the adapters in a separate knowledge composition step. We show that by separating the two stages, i.e., k"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.00247","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/2005.00247/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":"2026-07-05T02:09:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XSLXNkP9AWTlUTk+D4iN+7iwG1djbH7VswmL8BzN1kYCX7/nu020fTAmEdcY1AxgFcYzwxRcHecwY/tl1NxRDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:23:28.775256Z"},"content_sha256":"3a12dfd2d03ed31da45de2f80608785d657073599015e997bfc54143c0151158","schema_version":"1.0","event_id":"sha256:3a12dfd2d03ed31da45de2f80608785d657073599015e997bfc54143c0151158"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/bundle.json","state_url":"https://pith.science/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/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":"2026-07-06T19:23:28Z","links":{"resolver":"https://pith.science/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM","bundle":"https://pith.science/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/bundle.json","state":"https://pith.science/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MNNWJO3YLRMPWVA5EX2ADTZMPM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:MNNWJO3YLRMPWVA5EX2ADTZMPM","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":"2c69db1deeb4f88e9e1bd03163773c56d0efe9609585c8178ea56d44e1ef2535","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-01T07:03:42Z","title_canon_sha256":"279bbd39113cd89ab11478010ad7f817bb8ec0da24e0589af13ce50cea53c8db"},"schema_version":"1.0","source":{"id":"2005.00247","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.00247","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"arxiv_version","alias_value":"2005.00247v3","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.00247","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_12","alias_value":"MNNWJO3YLRMP","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_16","alias_value":"MNNWJO3YLRMPWVA5","created_at":"2026-07-05T02:09:39Z"},{"alias_kind":"pith_short_8","alias_value":"MNNWJO3Y","created_at":"2026-07-05T02:09:39Z"}],"graph_snapshots":[{"event_id":"sha256:3a12dfd2d03ed31da45de2f80608785d657073599015e997bfc54143c0151158","target":"graph","created_at":"2026-07-05T02:09:39Z","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/2005.00247/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sequential fine-tuning and multi-task learning are methods aiming to incorporate knowledge from multiple tasks; however, they suffer from catastrophic forgetting and difficulties in dataset balancing. To address these shortcomings, we propose AdapterFusion, a new two stage learning algorithm that leverages knowledge from multiple tasks. First, in the knowledge extraction stage we learn task specific parameters called adapters, that encapsulate the task-specific information. We then combine the adapters in a separate knowledge composition step. We show that by separating the two stages, i.e., k","authors_text":"Aishwarya Kamath, Andreas R\\\"uckl\\'e, Iryna Gurevych, Jonas Pfeiffer, Kyunghyun Cho","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-01T07:03:42Z","title":"AdapterFusion: Non-Destructive Task Composition for Transfer Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.00247","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:bfe78a0808f00512ee26d427877bbd6c4cdb35843e9dca2427d6ec46c756ed78","target":"record","created_at":"2026-07-05T02:09:39Z","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":"2c69db1deeb4f88e9e1bd03163773c56d0efe9609585c8178ea56d44e1ef2535","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-01T07:03:42Z","title_canon_sha256":"279bbd39113cd89ab11478010ad7f817bb8ec0da24e0589af13ce50cea53c8db"},"schema_version":"1.0","source":{"id":"2005.00247","kind":"arxiv","version":3}},"canonical_sha256":"635b64bb785c58fb541d25f401cf2c7b27bee3346cf181ca51c98f17973019fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"635b64bb785c58fb541d25f401cf2c7b27bee3346cf181ca51c98f17973019fb","first_computed_at":"2026-07-05T02:09:39.147362Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:09:39.147362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8aQWHYeDh/07wd9+tJ6BvkVAmqIv3oZjWEXGpiepGWW0DZUuutZ4XaD8ihbJ+6lYE+hqA+Lg1RCgRVFSg0VxDg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:09:39.147704Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.00247","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bfe78a0808f00512ee26d427877bbd6c4cdb35843e9dca2427d6ec46c756ed78","sha256:3a12dfd2d03ed31da45de2f80608785d657073599015e997bfc54143c0151158"],"state_sha256":"f808489eefe723aa37b5fa9aa658d5134d1eadc50115f87dd111a088faf10db7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ueFlmA5q+7J6OqE7ZWzPgVNBXq7z9yTVOokOuLa8vwqm1WUNXs7ak8oH5HF7dm1RBbYA4ESvOHTwcK3kUiSWAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T19:23:28.777193Z","bundle_sha256":"bbcdb9fe0eab516cf48d5ce53f25b0c6a52a20556cc90b55ef1c16b877068ad5"}}