{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:24TDR375SOMGMRKOA7JCE24IYN","short_pith_number":"pith:24TDR375","schema_version":"1.0","canonical_sha256":"d72638effd939866454e07d2226b88c34dea691c98c1c44e6dcb5248885837a6","source":{"kind":"arxiv","id":"2505.16938","version":3},"attestation_state":"computed","paper":{"title":"InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.CV"],"primary_cat":"cs.AI","authors_text":"Bowen Zhou, Dongzhan Zhou, InternAgent Team: Bo Zhang, Jiakang Yuan, Jinyao Liu, Lei Bai, Meng Li, Peng Ye, Runmin Ma, Shaowei Hou, Shiyang Feng, Shufei Zhang, Songtao Huang, Tianshuo Peng, Wangli Ouyang, Xiangchao Yan, Xiangyu Yue, Xiaohan He, Xiaosong Wang, Yilan Zhang, Yusong Hu, Zheng Nie, Zhilong Wang, Zhiyin Yu, Zhongying Tu","submitted_at":"2025-05-22T17:27:43Z","abstract_excerpt":"Artificial Intelligence (AI) is accelerating the transformation of scientific research paradigms, not only enhancing research efficiency but also driving innovation. We introduce InternAgent, a unified closed-loop multi-agent framework to conduct Autonomous Scientific Research (ASR) across various scientific research fields, enabling researchers to tackle complicated problems in these fields with unprecedented speed and precision. InternAgent highlights three key advantages: 1) Scalability: InternAgent has demonstrated its versatility across 12 scientific research tasks, capable of generating "},"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":"2505.16938","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-05-22T17:27:43Z","cross_cats_sorted":["cs.CL","cs.CV"],"title_canon_sha256":"08c5c056d982c6fe27c14aace11ccfff318d96a9031c16b4d116d7f14ac1c285","abstract_canon_sha256":"075ab69831a211cf082e8f4c10757fad58dc220b197a9f47dd1ffee57d0020bc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:41:24.675934Z","signature_b64":"DkB/yvKCjELhXhg85ErhlhjrjfR7QtPu0ubEK5qRo50GvrCdkahMKTqypRDD7WXwiBMgtANwMyjONPqcZye+Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d72638effd939866454e07d2226b88c34dea691c98c1c44e6dcb5248885837a6","last_reissued_at":"2026-07-05T11:41:24.675375Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:41:24.675375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.CV"],"primary_cat":"cs.AI","authors_text":"Bowen Zhou, Dongzhan Zhou, InternAgent Team: Bo Zhang, Jiakang Yuan, Jinyao Liu, Lei Bai, Meng Li, Peng Ye, Runmin Ma, Shaowei Hou, Shiyang Feng, Shufei Zhang, Songtao Huang, Tianshuo Peng, Wangli Ouyang, Xiangchao Yan, Xiangyu Yue, Xiaohan He, Xiaosong Wang, Yilan Zhang, Yusong Hu, Zheng Nie, Zhilong Wang, Zhiyin Yu, Zhongying Tu","submitted_at":"2025-05-22T17:27:43Z","abstract_excerpt":"Artificial Intelligence (AI) is accelerating the transformation of scientific research paradigms, not only enhancing research efficiency but also driving innovation. We introduce InternAgent, a unified closed-loop multi-agent framework to conduct Autonomous Scientific Research (ASR) across various scientific research fields, enabling researchers to tackle complicated problems in these fields with unprecedented speed and precision. InternAgent highlights three key advantages: 1) Scalability: InternAgent has demonstrated its versatility across 12 scientific research tasks, capable of generating "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.16938","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/2505.16938/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":"2505.16938","created_at":"2026-07-05T11:41:24.675445+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.16938v3","created_at":"2026-07-05T11:41:24.675445+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.16938","created_at":"2026-07-05T11:41:24.675445+00:00"},{"alias_kind":"pith_short_12","alias_value":"24TDR375SOMG","created_at":"2026-07-05T11:41:24.675445+00:00"},{"alias_kind":"pith_short_16","alias_value":"24TDR375SOMGMRKO","created_at":"2026-07-05T11:41:24.675445+00:00"},{"alias_kind":"pith_short_8","alias_value":"24TDR375","created_at":"2026-07-05T11:41:24.675445+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":17,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.24177","citing_title":"Agon: An Autonomous Large-Scale Omnidisciplinary Research System Built on Prompt Economy","ref_index":23,"is_internal_anchor":false},{"citing_arxiv_id":"2606.07301","citing_title":"Structure-guided taxonomic placement of divergent RNA viruses with ViraClass","ref_index":2,"is_internal_anchor":false},{"citing_arxiv_id":"2606.06473","citing_title":"MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery","ref_index":4,"is_internal_anchor":false},{"citing_arxiv_id":"2606.03248","citing_title":"Investigating Novice Researchers' Perceptions of Research Privacy Within LLM-Assisted Workflows","ref_index":91,"is_internal_anchor":false},{"citing_arxiv_id":"2606.31478","citing_title":"One Reflection Is Not Enough: Self-Correcting Autonomous Research via Multi-Hypothesis Failure Attribution","ref_index":116,"is_internal_anchor":false},{"citing_arxiv_id":"2605.27873","citing_title":"AIBuildAI-2: A Knowledge-Enhanced Agent for Automatically Building AI Models","ref_index":34,"is_internal_anchor":false},{"citing_arxiv_id":"2605.22878","citing_title":"SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research","ref_index":38,"is_internal_anchor":false},{"citing_arxiv_id":"2509.23986","citing_title":"TusoAI: Agentic Optimization for Scientific Methods","ref_index":37,"is_internal_anchor":false},{"citing_arxiv_id":"2512.01089","citing_title":"CodeDistiller: Automatically Generating Code Libraries for Scientific Coding Agents","ref_index":24,"is_internal_anchor":false},{"citing_arxiv_id":"2605.18661","citing_title":"AI for Auto-Research: Roadmap & User Guide","ref_index":249,"is_internal_anchor":false},{"citing_arxiv_id":"2507.11810","citing_title":"Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator","ref_index":172,"is_internal_anchor":false},{"citing_arxiv_id":"2601.05930","citing_title":"Can We Predict Before Executing Machine Learning Agents?","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2605.10813","citing_title":"NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation","ref_index":28,"is_internal_anchor":false},{"citing_arxiv_id":"2604.20622","citing_title":"pAI/MSc: ML Theory Research with Humans on the Loop","ref_index":70,"is_internal_anchor":false},{"citing_arxiv_id":"2604.14116","citing_title":"TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration","ref_index":43,"is_internal_anchor":false},{"citing_arxiv_id":"2604.14455","citing_title":"AIBuildAI: An AI Agent for Automatically Building AI Models","ref_index":29,"is_internal_anchor":false},{"citing_arxiv_id":"2604.17309","citing_title":"Knows: Agent-Native Structured Research Representations","ref_index":8,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN","json":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN.json","graph_json":"https://pith.science/api/pith-number/24TDR375SOMGMRKOA7JCE24IYN/graph.json","events_json":"https://pith.science/api/pith-number/24TDR375SOMGMRKOA7JCE24IYN/events.json","paper":"https://pith.science/paper/24TDR375"},"agent_actions":{"view_html":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN","download_json":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN.json","view_paper":"https://pith.science/paper/24TDR375","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.16938&json=true","fetch_graph":"https://pith.science/api/pith-number/24TDR375SOMGMRKOA7JCE24IYN/graph.json","fetch_events":"https://pith.science/api/pith-number/24TDR375SOMGMRKOA7JCE24IYN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN/action/storage_attestation","attest_author":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN/action/author_attestation","sign_citation":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN/action/citation_signature","submit_replication":"https://pith.science/pith/24TDR375SOMGMRKOA7JCE24IYN/action/replication_record"}},"created_at":"2026-07-05T11:41:24.675445+00:00","updated_at":"2026-07-05T11:41:24.675445+00:00"}