{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:XPZMQSM6TWIZWKFFV6NNEYUU7W","short_pith_number":"pith:XPZMQSM6","schema_version":"1.0","canonical_sha256":"bbf2c8499e9d919b28a5af9ad26294fd84ba840cf9cadec755a2510fd559fd45","source":{"kind":"arxiv","id":"2310.08367","version":4},"attestation_state":"computed","paper":{"title":"MCU: An Evaluation Framework for Open-Ended Game Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.CV","cs.LG"],"primary_cat":"cs.AI","authors_text":"Haowei Lin, Kaichen He, Xinyue Zheng, Yitao Liang, Zihao Wang, Zilong Zheng","submitted_at":"2023-10-12T14:38:25Z","abstract_excerpt":"Developing AI agents capable of interacting with open-world environments to solve diverse tasks is a compelling challenge. However, evaluating such open-ended agents remains difficult, with current benchmarks facing scalability limitations. To address this, we introduce Minecraft Universe (MCU), a comprehensive evaluation framework set within the open-world video game Minecraft. MCU incorporates three key components: (1) an expanding collection of 3,452 composable atomic tasks that encompasses 11 major categories and 41 subcategories of challenges; (2) a task composition mechanism capable of g"},"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":"2310.08367","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-10-12T14:38:25Z","cross_cats_sorted":["cs.CL","cs.CV","cs.LG"],"title_canon_sha256":"81a6ba10a5c976bf26888a1e85a9271d7b38574f266e9f31e95e33921c20bb88","abstract_canon_sha256":"891cc025193bb6fb25924204c29ce8e1658a6b4fd8eaf5eafe45685f7436bdce"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:22.749740Z","signature_b64":"v0lePqAyDhCvxzA9YyvE9cdVgFAZYazoeMITBfDjmJBklYsDoc05Q0K5h+GRodeAOWGI+J2wYNVcykNcr89gBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bbf2c8499e9d919b28a5af9ad26294fd84ba840cf9cadec755a2510fd559fd45","last_reissued_at":"2026-07-05T11:14:22.749254Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:22.749254Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MCU: An Evaluation Framework for Open-Ended Game Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.CV","cs.LG"],"primary_cat":"cs.AI","authors_text":"Haowei Lin, Kaichen He, Xinyue Zheng, Yitao Liang, Zihao Wang, Zilong Zheng","submitted_at":"2023-10-12T14:38:25Z","abstract_excerpt":"Developing AI agents capable of interacting with open-world environments to solve diverse tasks is a compelling challenge. However, evaluating such open-ended agents remains difficult, with current benchmarks facing scalability limitations. To address this, we introduce Minecraft Universe (MCU), a comprehensive evaluation framework set within the open-world video game Minecraft. MCU incorporates three key components: (1) an expanding collection of 3,452 composable atomic tasks that encompasses 11 major categories and 41 subcategories of challenges; (2) a task composition mechanism capable of g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08367","kind":"arxiv","version":4},"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/2310.08367/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":"2310.08367","created_at":"2026-07-05T11:14:22.749311+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.08367v4","created_at":"2026-07-05T11:14:22.749311+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08367","created_at":"2026-07-05T11:14:22.749311+00:00"},{"alias_kind":"pith_short_12","alias_value":"XPZMQSM6TWIZ","created_at":"2026-07-05T11:14:22.749311+00:00"},{"alias_kind":"pith_short_16","alias_value":"XPZMQSM6TWIZWKFF","created_at":"2026-07-05T11:14:22.749311+00:00"},{"alias_kind":"pith_short_8","alias_value":"XPZMQSM6","created_at":"2026-07-05T11:14:22.749311+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":8,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2412.02125","citing_title":"Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies","ref_index":35,"is_internal_anchor":false},{"citing_arxiv_id":"2605.20246","citing_title":"GROW: Aligning GRPO with State-Action Modeling for Open-World VLM Agents","ref_index":13,"is_internal_anchor":false},{"citing_arxiv_id":"2605.20246","citing_title":"GROW: Aligning GRPO with State-Action Modeling for Open-World VLM Agents","ref_index":13,"is_internal_anchor":false},{"citing_arxiv_id":"2507.01925","citing_title":"A Survey on Vision-Language-Action Models: An Action Tokenization Perspective","ref_index":263,"is_internal_anchor":false},{"citing_arxiv_id":"2302.01560","citing_title":"Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents","ref_index":24,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09965","citing_title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","ref_index":224,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09965","citing_title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","ref_index":224,"is_internal_anchor":false},{"citing_arxiv_id":"2604.18975","citing_title":"Gated Coordination for Efficient Multi-Agent Collaboration in Minecraft Game","ref_index":19,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W","json":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W.json","graph_json":"https://pith.science/api/pith-number/XPZMQSM6TWIZWKFFV6NNEYUU7W/graph.json","events_json":"https://pith.science/api/pith-number/XPZMQSM6TWIZWKFFV6NNEYUU7W/events.json","paper":"https://pith.science/paper/XPZMQSM6"},"agent_actions":{"view_html":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W","download_json":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W.json","view_paper":"https://pith.science/paper/XPZMQSM6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.08367&json=true","fetch_graph":"https://pith.science/api/pith-number/XPZMQSM6TWIZWKFFV6NNEYUU7W/graph.json","fetch_events":"https://pith.science/api/pith-number/XPZMQSM6TWIZWKFFV6NNEYUU7W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W/action/storage_attestation","attest_author":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W/action/author_attestation","sign_citation":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W/action/citation_signature","submit_replication":"https://pith.science/pith/XPZMQSM6TWIZWKFFV6NNEYUU7W/action/replication_record"}},"created_at":"2026-07-05T11:14:22.749311+00:00","updated_at":"2026-07-05T11:14:22.749311+00:00"}