{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:RAITF22RR2K4EBATRKPMY4ECTY","short_pith_number":"pith:RAITF22R","canonical_record":{"source":{"id":"2503.22473","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-28T14:33:29Z","cross_cats_sorted":[],"title_canon_sha256":"da9c3b29dda4c323f04233027371a8d4f2f615d560bdb01cc9db362ac86ab369","abstract_canon_sha256":"85ba681cd90eacfd3d5d41acffe617c4384877b2191ebe0975ed6df14b265b2a"},"schema_version":"1.0"},"canonical_sha256":"881132eb518e95c204138a9ecc70829e2df1b32c57ec347db320860599e084ef","source":{"kind":"arxiv","id":"2503.22473","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.22473","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.22473v1","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.22473","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_12","alias_value":"RAITF22RR2K4","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_16","alias_value":"RAITF22RR2K4EBAT","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_8","alias_value":"RAITF22R","created_at":"2026-07-05T10:41:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:RAITF22RR2K4EBATRKPMY4ECTY","target":"record","payload":{"canonical_record":{"source":{"id":"2503.22473","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-28T14:33:29Z","cross_cats_sorted":[],"title_canon_sha256":"da9c3b29dda4c323f04233027371a8d4f2f615d560bdb01cc9db362ac86ab369","abstract_canon_sha256":"85ba681cd90eacfd3d5d41acffe617c4384877b2191ebe0975ed6df14b265b2a"},"schema_version":"1.0"},"canonical_sha256":"881132eb518e95c204138a9ecc70829e2df1b32c57ec347db320860599e084ef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:05.277723Z","signature_b64":"RhNtyH3Ednu2q0cMU77MHuFlEgiDmm4kufnYEF/eVx/6zMGLhV6dcya/a0f4/1F1X5RolKLoSEoWN+4S2yDaCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"881132eb518e95c204138a9ecc70829e2df1b32c57ec347db320860599e084ef","last_reissued_at":"2026-07-05T10:41:05.277232Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:05.277232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.22473","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":"2026-07-05T10:41:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GfNmtJ5pbh/QFRVVSCH3dLyJc2LXEjntkivBqe1HHImaTBpBQ1rv9BhkLTj58tQKcQNcWqGKhHk3keOngL39Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T21:23:49.854207Z"},"content_sha256":"529131e31a12611565125846fa4d36ceecbe38252b203852f2b4abe896d37923","schema_version":"1.0","event_id":"sha256:529131e31a12611565125846fa4d36ceecbe38252b203852f2b4abe896d37923"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:RAITF22RR2K4EBATRKPMY4ECTY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"WorkTeam: Constructing Workflows from Natural Language with Multi-Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hanchao Liu, Rongjun Li, Weimin Xiong, Wei Peng, Ziyu Zhou","submitted_at":"2025-03-28T14:33:29Z","abstract_excerpt":"Workflows play a crucial role in enhancing enterprise efficiency by orchestrating complex processes with multiple tools or components. However, hand-crafted workflow construction requires expert knowledge, presenting significant technical barriers. Recent advancements in Large Language Models (LLMs) have improved the generation of workflows from natural language instructions (aka NL2Workflow), yet existing single LLM agent-based methods face performance degradation on complex tasks due to the need for specialized knowledge and the strain of task-switching. To tackle these challenges, we propos"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.22473","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/2503.22473/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":"2026-07-05T10:41:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ooTHuhJyHp/kWjvUkxDjlrOJ02HHmRznKfDEKDi054aDclSvE74avMuL1DFzvcrhOZ1qaXkKiJ/sBj9WKKxCCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T21:23:49.854596Z"},"content_sha256":"8110874c027ba3076457dd236246ee9ab8ce765dacc032ad439dbed8ffe08791","schema_version":"1.0","event_id":"sha256:8110874c027ba3076457dd236246ee9ab8ce765dacc032ad439dbed8ffe08791"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RAITF22RR2K4EBATRKPMY4ECTY/bundle.json","state_url":"https://pith.science/pith/RAITF22RR2K4EBATRKPMY4ECTY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RAITF22RR2K4EBATRKPMY4ECTY/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":"2026-07-09T21:23:49Z","links":{"resolver":"https://pith.science/pith/RAITF22RR2K4EBATRKPMY4ECTY","bundle":"https://pith.science/pith/RAITF22RR2K4EBATRKPMY4ECTY/bundle.json","state":"https://pith.science/pith/RAITF22RR2K4EBATRKPMY4ECTY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RAITF22RR2K4EBATRKPMY4ECTY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RAITF22RR2K4EBATRKPMY4ECTY","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":"85ba681cd90eacfd3d5d41acffe617c4384877b2191ebe0975ed6df14b265b2a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-28T14:33:29Z","title_canon_sha256":"da9c3b29dda4c323f04233027371a8d4f2f615d560bdb01cc9db362ac86ab369"},"schema_version":"1.0","source":{"id":"2503.22473","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.22473","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.22473v1","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.22473","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_12","alias_value":"RAITF22RR2K4","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_16","alias_value":"RAITF22RR2K4EBAT","created_at":"2026-07-05T10:41:05Z"},{"alias_kind":"pith_short_8","alias_value":"RAITF22R","created_at":"2026-07-05T10:41:05Z"}],"graph_snapshots":[{"event_id":"sha256:8110874c027ba3076457dd236246ee9ab8ce765dacc032ad439dbed8ffe08791","target":"graph","created_at":"2026-07-05T10:41:05Z","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/2503.22473/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Workflows play a crucial role in enhancing enterprise efficiency by orchestrating complex processes with multiple tools or components. However, hand-crafted workflow construction requires expert knowledge, presenting significant technical barriers. Recent advancements in Large Language Models (LLMs) have improved the generation of workflows from natural language instructions (aka NL2Workflow), yet existing single LLM agent-based methods face performance degradation on complex tasks due to the need for specialized knowledge and the strain of task-switching. To tackle these challenges, we propos","authors_text":"Hanchao Liu, Rongjun Li, Weimin Xiong, Wei Peng, Ziyu Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-28T14:33:29Z","title":"WorkTeam: Constructing Workflows from Natural Language with Multi-Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.22473","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":"sha256:529131e31a12611565125846fa4d36ceecbe38252b203852f2b4abe896d37923","target":"record","created_at":"2026-07-05T10:41:05Z","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":"85ba681cd90eacfd3d5d41acffe617c4384877b2191ebe0975ed6df14b265b2a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-28T14:33:29Z","title_canon_sha256":"da9c3b29dda4c323f04233027371a8d4f2f615d560bdb01cc9db362ac86ab369"},"schema_version":"1.0","source":{"id":"2503.22473","kind":"arxiv","version":1}},"canonical_sha256":"881132eb518e95c204138a9ecc70829e2df1b32c57ec347db320860599e084ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"881132eb518e95c204138a9ecc70829e2df1b32c57ec347db320860599e084ef","first_computed_at":"2026-07-05T10:41:05.277232Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:41:05.277232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RhNtyH3Ednu2q0cMU77MHuFlEgiDmm4kufnYEF/eVx/6zMGLhV6dcya/a0f4/1F1X5RolKLoSEoWN+4S2yDaCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:41:05.277723Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.22473","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:529131e31a12611565125846fa4d36ceecbe38252b203852f2b4abe896d37923","sha256:8110874c027ba3076457dd236246ee9ab8ce765dacc032ad439dbed8ffe08791"],"state_sha256":"6623d23d0bb2e69fbeff8bd28e1263b6be3bd62b9bfc480f2fda68d855a09daf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lqhg0PrUR9EaHBun/RzVS56bBCmQQAZ8fznwI8IZrOKHAXGM/dEeGc39tzJMtuWO/ZCfA54ZeV2YA3Occ5VtCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T21:23:49.857648Z","bundle_sha256":"a527c4e7382f06f665f728748f76d9248fb2b842ad2ac8a083dd437a448f5bad"}}