{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XGJRORL2NYDUJLO3SAC5MBOFJE","short_pith_number":"pith:XGJRORL2","canonical_record":{"source":{"id":"2605.28424","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T12:54:33Z","cross_cats_sorted":[],"title_canon_sha256":"05ff34eea5646bf3525aea5fba8e75231b34e4afa87cb02b70bd93cbb7498433","abstract_canon_sha256":"82a4fb80f702c126ededc4505ab3650292ed55092b826673a0baacdac72433d0"},"schema_version":"1.0"},"canonical_sha256":"b99317457a6e0744addb9005d605c5492ed4a5ddd43e25885548efeec16f2279","source":{"kind":"arxiv","id":"2605.28424","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28424","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28424v1","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28424","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_12","alias_value":"XGJRORL2NYDU","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_16","alias_value":"XGJRORL2NYDUJLO3","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_8","alias_value":"XGJRORL2","created_at":"2026-05-28T01:05:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XGJRORL2NYDUJLO3SAC5MBOFJE","target":"record","payload":{"canonical_record":{"source":{"id":"2605.28424","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T12:54:33Z","cross_cats_sorted":[],"title_canon_sha256":"05ff34eea5646bf3525aea5fba8e75231b34e4afa87cb02b70bd93cbb7498433","abstract_canon_sha256":"82a4fb80f702c126ededc4505ab3650292ed55092b826673a0baacdac72433d0"},"schema_version":"1.0"},"canonical_sha256":"b99317457a6e0744addb9005d605c5492ed4a5ddd43e25885548efeec16f2279","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T01:05:17.790911Z","signature_b64":"Gw1m+AAwCK2nh0Pwt+Oum2WEcZvlC3Vg69aaXStYBlZ3mJ2q2ckdUSRPUX58YlXiviOu7CMKakT+fdRzdkdmBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b99317457a6e0744addb9005d605c5492ed4a5ddd43e25885548efeec16f2279","last_reissued_at":"2026-05-28T01:05:17.790493Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T01:05:17.790493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.28424","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":"2026-05-28T01:05:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZZfrirTlHO5emQp92x+4q/JYW0SfhMrO3qywGvubEPei9RypJxjxCjnYr2c7Z74H96XO/yxaAbhxAofEt/IpBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T16:32:01.913775Z"},"content_sha256":"cc86f3587b7a802a20bd0ae5fb094d21d4a8800163f071f94a27699d0357f9d6","schema_version":"1.0","event_id":"sha256:cc86f3587b7a802a20bd0ae5fb094d21d4a8800163f071f94a27699d0357f9d6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XGJRORL2NYDUJLO3SAC5MBOFJE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chengcheng Han, Jianxiang Yu, Jiapeng Zhu, Qi Gu, Weining Qian, Xiang Li, Xunliang Cai, Yibo Zhao","submitted_at":"2026-05-27T12:54:33Z","abstract_excerpt":"Equipping large language models with explicit skills has emerged as a promising paradigm for enabling autonomous agents to solve complex tasks. Agent skills can be inherently divided into general skills for broad cognitive transfer and task-specific skills for dynamic execution. However, existing skill-based reinforcement learning (RL) methods typically force a rigid choice between full externalization, which incurs prohibitive context overhead, and full internalization, which risks overfitting and knowledge conflicts. To address this dilemma, we propose Skill0.5, a novel agentic RL framework "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28424","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/2605.28424/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":"2026-05-28T01:05:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AetkbRWrziFXcgP9gKpLyJ6cJyGiB3i4lJlFyy43v8ktrm0yRMWvlXrDoIFBOsbOqNVcy6KHiYNS75ZybBIUDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T16:32:01.914134Z"},"content_sha256":"56a65109c941aa18a781f9a475cf513a893e4dbe7dbb07a1aae9c831770826cc","schema_version":"1.0","event_id":"sha256:56a65109c941aa18a781f9a475cf513a893e4dbe7dbb07a1aae9c831770826cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/bundle.json","state_url":"https://pith.science/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/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":"2026-06-29T16:32:01Z","links":{"resolver":"https://pith.science/pith/XGJRORL2NYDUJLO3SAC5MBOFJE","bundle":"https://pith.science/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/bundle.json","state":"https://pith.science/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XGJRORL2NYDUJLO3SAC5MBOFJE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XGJRORL2NYDUJLO3SAC5MBOFJE","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":"82a4fb80f702c126ededc4505ab3650292ed55092b826673a0baacdac72433d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T12:54:33Z","title_canon_sha256":"05ff34eea5646bf3525aea5fba8e75231b34e4afa87cb02b70bd93cbb7498433"},"schema_version":"1.0","source":{"id":"2605.28424","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28424","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28424v1","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28424","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_12","alias_value":"XGJRORL2NYDU","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_16","alias_value":"XGJRORL2NYDUJLO3","created_at":"2026-05-28T01:05:17Z"},{"alias_kind":"pith_short_8","alias_value":"XGJRORL2","created_at":"2026-05-28T01:05:17Z"}],"graph_snapshots":[{"event_id":"sha256:56a65109c941aa18a781f9a475cf513a893e4dbe7dbb07a1aae9c831770826cc","target":"graph","created_at":"2026-05-28T01:05:17Z","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/2605.28424/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Equipping large language models with explicit skills has emerged as a promising paradigm for enabling autonomous agents to solve complex tasks. Agent skills can be inherently divided into general skills for broad cognitive transfer and task-specific skills for dynamic execution. However, existing skill-based reinforcement learning (RL) methods typically force a rigid choice between full externalization, which incurs prohibitive context overhead, and full internalization, which risks overfitting and knowledge conflicts. To address this dilemma, we propose Skill0.5, a novel agentic RL framework ","authors_text":"Chengcheng Han, Jianxiang Yu, Jiapeng Zhu, Qi Gu, Weining Qian, Xiang Li, Xunliang Cai, Yibo Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T12:54:33Z","title":"Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28424","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:cc86f3587b7a802a20bd0ae5fb094d21d4a8800163f071f94a27699d0357f9d6","target":"record","created_at":"2026-05-28T01:05:17Z","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":"82a4fb80f702c126ededc4505ab3650292ed55092b826673a0baacdac72433d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T12:54:33Z","title_canon_sha256":"05ff34eea5646bf3525aea5fba8e75231b34e4afa87cb02b70bd93cbb7498433"},"schema_version":"1.0","source":{"id":"2605.28424","kind":"arxiv","version":1}},"canonical_sha256":"b99317457a6e0744addb9005d605c5492ed4a5ddd43e25885548efeec16f2279","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b99317457a6e0744addb9005d605c5492ed4a5ddd43e25885548efeec16f2279","first_computed_at":"2026-05-28T01:05:17.790493Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:05:17.790493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Gw1m+AAwCK2nh0Pwt+Oum2WEcZvlC3Vg69aaXStYBlZ3mJ2q2ckdUSRPUX58YlXiviOu7CMKakT+fdRzdkdmBw==","signature_status":"signed_v1","signed_at":"2026-05-28T01:05:17.790911Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.28424","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc86f3587b7a802a20bd0ae5fb094d21d4a8800163f071f94a27699d0357f9d6","sha256:56a65109c941aa18a781f9a475cf513a893e4dbe7dbb07a1aae9c831770826cc"],"state_sha256":"b314aefb74a5086eb220a8ea00cb2534857b127069305dd746b1ade30b43a561"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6PisEpHprcNQ3LseSKIFN+lEd+C8zhT09zUJBlpDiQxo6/fmpxiGz/FiDVONm66dHTo7gbXSPhT+uQfg9u5cCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T16:32:01.916043Z","bundle_sha256":"8d099596d3656ab571e6753f2a4b8a2e85cd7cf1b69fb8e086de1e99b11ca809"}}