{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:C7TTROWSLE7OPZO263EE3BT624","short_pith_number":"pith:C7TTROWS","canonical_record":{"source":{"id":"2205.12648","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-25T10:44:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c74955abfaf8fc529d1c792ca425d96c62a2d879972a934d218316330a84c303","abstract_canon_sha256":"6d0f6d75cde2ac8ae04b0bf4031a06a5ded20e1007058c5a0b044ccec7549771"},"schema_version":"1.0"},"canonical_sha256":"17e738bad2593ee7e5daf6c84d867ed70ed2cc1d14f322f0de607c7c1036e6ed","source":{"kind":"arxiv","id":"2205.12648","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12648","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12648v1","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12648","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_12","alias_value":"C7TTROWSLE7O","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"C7TTROWSLE7OPZO2","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"C7TTROWS","created_at":"2026-07-05T04:26:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:C7TTROWSLE7OPZO263EE3BT624","target":"record","payload":{"canonical_record":{"source":{"id":"2205.12648","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-25T10:44:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c74955abfaf8fc529d1c792ca425d96c62a2d879972a934d218316330a84c303","abstract_canon_sha256":"6d0f6d75cde2ac8ae04b0bf4031a06a5ded20e1007058c5a0b044ccec7549771"},"schema_version":"1.0"},"canonical_sha256":"17e738bad2593ee7e5daf6c84d867ed70ed2cc1d14f322f0de607c7c1036e6ed","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:28.452752Z","signature_b64":"c3b8ZaJM3yzwnDl3DP7mzvv3ImiNR/LJcNlrsX9srRk0mSd1LsowPvXcntF3b6c9fEv4h58bCisIxd37xT54BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17e738bad2593ee7e5daf6c84d867ed70ed2cc1d14f322f0de607c7c1036e6ed","last_reissued_at":"2026-07-05T04:26:28.452227Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:28.452227Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.12648","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:26:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fnlXaayg3s4DrbqR5t7BRbRDmN6oEo+vjmA1E4N4GD3AWpvUSzqT/8bTzSQe7aR42NmdO2CsU18xubkPAvGXDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:19:49.688140Z"},"content_sha256":"9dfe6566e0686bf3312e7cdc58c49620ee778b4e832ef1cb52f78350cf6d6480","schema_version":"1.0","event_id":"sha256:9dfe6566e0686bf3312e7cdc58c49620ee778b4e832ef1cb52f78350cf6d6480"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:C7TTROWSLE7OPZO263EE3BT624","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Aleksandra Faust, Honglak Lee, Hyunjae Woo, Izzeddin Gur, Jongwook Choi, lyubing qiang, Sungryull Sohn","submitted_at":"2022-05-25T10:44:25Z","abstract_excerpt":"We tackle real-world problems with complex structures beyond the pixel-based game or simulator. We formulate it as a few-shot reinforcement learning problem where a task is characterized by a subtask graph that defines a set of subtasks and their dependencies that are unknown to the agent. Different from the previous meta-rl methods trying to directly infer the unstructured task embedding, our multi-task subtask graph inferencer (MTSGI) first infers the common high-level task structure in terms of the subtask graph from the training tasks, and use it as a prior to improve the task inference in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12648","kind":"arxiv","version":1},"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/2205.12648/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":"2026-07-05T04:26:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ILUS1NZbsW2xK9CbOBOwzFUzGF92dbc0CugIYi/x1PGnbjS3IENut51cTLoQGFsu61vOjmeuDaaSyBZRpCSlCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:19:49.688742Z"},"content_sha256":"b435526a79b4b9a214554396ffef71db0e6d03b06c3376670dbeea45e2f62f03","schema_version":"1.0","event_id":"sha256:b435526a79b4b9a214554396ffef71db0e6d03b06c3376670dbeea45e2f62f03"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C7TTROWSLE7OPZO263EE3BT624/bundle.json","state_url":"https://pith.science/pith/C7TTROWSLE7OPZO263EE3BT624/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C7TTROWSLE7OPZO263EE3BT624/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":"2026-07-06T23:19:49Z","links":{"resolver":"https://pith.science/pith/C7TTROWSLE7OPZO263EE3BT624","bundle":"https://pith.science/pith/C7TTROWSLE7OPZO263EE3BT624/bundle.json","state":"https://pith.science/pith/C7TTROWSLE7OPZO263EE3BT624/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C7TTROWSLE7OPZO263EE3BT624/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:C7TTROWSLE7OPZO263EE3BT624","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":"6d0f6d75cde2ac8ae04b0bf4031a06a5ded20e1007058c5a0b044ccec7549771","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-25T10:44:25Z","title_canon_sha256":"c74955abfaf8fc529d1c792ca425d96c62a2d879972a934d218316330a84c303"},"schema_version":"1.0","source":{"id":"2205.12648","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12648","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12648v1","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12648","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_12","alias_value":"C7TTROWSLE7O","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"C7TTROWSLE7OPZO2","created_at":"2026-07-05T04:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"C7TTROWS","created_at":"2026-07-05T04:26:28Z"}],"graph_snapshots":[{"event_id":"sha256:b435526a79b4b9a214554396ffef71db0e6d03b06c3376670dbeea45e2f62f03","target":"graph","created_at":"2026-07-05T04:26:28Z","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/2205.12648/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We tackle real-world problems with complex structures beyond the pixel-based game or simulator. We formulate it as a few-shot reinforcement learning problem where a task is characterized by a subtask graph that defines a set of subtasks and their dependencies that are unknown to the agent. Different from the previous meta-rl methods trying to directly infer the unstructured task embedding, our multi-task subtask graph inferencer (MTSGI) first infers the common high-level task structure in terms of the subtask graph from the training tasks, and use it as a prior to improve the task inference in","authors_text":"Aleksandra Faust, Honglak Lee, Hyunjae Woo, Izzeddin Gur, Jongwook Choi, lyubing qiang, Sungryull Sohn","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-25T10:44:25Z","title":"Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12648","kind":"arxiv","version":1},"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":"sha256:9dfe6566e0686bf3312e7cdc58c49620ee778b4e832ef1cb52f78350cf6d6480","target":"record","created_at":"2026-07-05T04:26:28Z","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":"6d0f6d75cde2ac8ae04b0bf4031a06a5ded20e1007058c5a0b044ccec7549771","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-25T10:44:25Z","title_canon_sha256":"c74955abfaf8fc529d1c792ca425d96c62a2d879972a934d218316330a84c303"},"schema_version":"1.0","source":{"id":"2205.12648","kind":"arxiv","version":1}},"canonical_sha256":"17e738bad2593ee7e5daf6c84d867ed70ed2cc1d14f322f0de607c7c1036e6ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17e738bad2593ee7e5daf6c84d867ed70ed2cc1d14f322f0de607c7c1036e6ed","first_computed_at":"2026-07-05T04:26:28.452227Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:28.452227Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c3b8ZaJM3yzwnDl3DP7mzvv3ImiNR/LJcNlrsX9srRk0mSd1LsowPvXcntF3b6c9fEv4h58bCisIxd37xT54BA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:28.452752Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.12648","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9dfe6566e0686bf3312e7cdc58c49620ee778b4e832ef1cb52f78350cf6d6480","sha256:b435526a79b4b9a214554396ffef71db0e6d03b06c3376670dbeea45e2f62f03"],"state_sha256":"cd667d3f8a57738259595ef8b0bdc503f583cfadc48a6a837576d883c6bccaed"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l4SJeUPOUJCZnnftcVvrviqXEiMsVtmbTQITJhKJ0sg5dHwkTS8j4egjc1BUmbg+Y+5FksR4SL+9E2expD9pBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T23:19:49.691409Z","bundle_sha256":"f10303108f7655a367bd774bdc471318ab3d6cae4f73f745f2da30456a348e57"}}