{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:EJJ6CX5JNFLCLV6G2WPCGX4NMH","short_pith_number":"pith:EJJ6CX5J","schema_version":"1.0","canonical_sha256":"2253e15fa9695625d7c6d59e235f8d61f153e08ab376a5d441001ba5aa02833b","source":{"kind":"arxiv","id":"2309.00986","version":1},"attestation_state":"computed","paper":{"title":"ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chen Cheng, Chenliang Li, Fei Huang, Haiyang Xu, Hehong Chen, Hongzhu Shi, Jingren Zhou, Ji Zhang, Ming Yan, Weizhou Shen, Wenmeng Zhou, Yingda Chen, Zhicheng Zhang, Zhikai Wu","submitted_at":"2023-09-02T16:50:30Z","abstract_excerpt":"Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further unleash the power of LLMs to accomplish complex tasks, there is a growing trend to build agent framework that equips LLMs, such as ChatGPT, with tool-use abilities to connect with massive external APIs. In this work, we introduce ModelScope-Agent, a general and customizable agent framework for real-world applications, based on open-source LLMs as controllers. It provides a user-friendly system library, with customizab"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2309.00986","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-09-02T16:50:30Z","cross_cats_sorted":[],"title_canon_sha256":"ad38e7ca837c965685b313d0fbec6431131bce68389fd4cd118bffd12cd61faf","abstract_canon_sha256":"31a05beb8abea9116ac8de91705d029667616d4fd96c6a84d9f87feccf0a143d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:47:30.654801Z","signature_b64":"8ynrFKjz3e0/Tn3+j8g7nLwji5gJ1jpJZuMJjxqYA0urhgL83JTZU6xK64KguEr7Y+DstK8lFGhQRNRsnAq2Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2253e15fa9695625d7c6d59e235f8d61f153e08ab376a5d441001ba5aa02833b","last_reissued_at":"2026-07-05T06:47:30.654257Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:47:30.654257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chen Cheng, Chenliang Li, Fei Huang, Haiyang Xu, Hehong Chen, Hongzhu Shi, Jingren Zhou, Ji Zhang, Ming Yan, Weizhou Shen, Wenmeng Zhou, Yingda Chen, Zhicheng Zhang, Zhikai Wu","submitted_at":"2023-09-02T16:50:30Z","abstract_excerpt":"Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further unleash the power of LLMs to accomplish complex tasks, there is a growing trend to build agent framework that equips LLMs, such as ChatGPT, with tool-use abilities to connect with massive external APIs. In this work, we introduce ModelScope-Agent, a general and customizable agent framework for real-world applications, based on open-source LLMs as controllers. It provides a user-friendly system library, with customizab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.00986","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/2309.00986/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2309.00986","created_at":"2026-07-05T06:47:30.654321+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.00986v1","created_at":"2026-07-05T06:47:30.654321+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.00986","created_at":"2026-07-05T06:47:30.654321+00:00"},{"alias_kind":"pith_short_12","alias_value":"EJJ6CX5JNFLC","created_at":"2026-07-05T06:47:30.654321+00:00"},{"alias_kind":"pith_short_16","alias_value":"EJJ6CX5JNFLCLV6G","created_at":"2026-07-05T06:47:30.654321+00:00"},{"alias_kind":"pith_short_8","alias_value":"EJJ6CX5J","created_at":"2026-07-05T06:47:30.654321+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2401.16158","citing_title":"Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception","ref_index":1,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH","json":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH.json","graph_json":"https://pith.science/api/pith-number/EJJ6CX5JNFLCLV6G2WPCGX4NMH/graph.json","events_json":"https://pith.science/api/pith-number/EJJ6CX5JNFLCLV6G2WPCGX4NMH/events.json","paper":"https://pith.science/paper/EJJ6CX5J"},"agent_actions":{"view_html":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH","download_json":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH.json","view_paper":"https://pith.science/paper/EJJ6CX5J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.00986&json=true","fetch_graph":"https://pith.science/api/pith-number/EJJ6CX5JNFLCLV6G2WPCGX4NMH/graph.json","fetch_events":"https://pith.science/api/pith-number/EJJ6CX5JNFLCLV6G2WPCGX4NMH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH/action/storage_attestation","attest_author":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH/action/author_attestation","sign_citation":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH/action/citation_signature","submit_replication":"https://pith.science/pith/EJJ6CX5JNFLCLV6G2WPCGX4NMH/action/replication_record"}},"created_at":"2026-07-05T06:47:30.654321+00:00","updated_at":"2026-07-05T06:47:30.654321+00:00"}