{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:BESANHKATNWG5A4WXYLGLU55SC","short_pith_number":"pith:BESANHKA","schema_version":"1.0","canonical_sha256":"0924069d409b6c6e8396be1665d3bd908870696f17f711e093ba513a69fc9743","source":{"kind":"arxiv","id":"2407.05377","version":1},"attestation_state":"computed","paper":{"title":"Collective Innovation in Groups of Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Cl\\'ement Moulin-Frier, Eleni Nisioti, Ida Momennejad, Pierre-Yves Oudeyer, Sebastian Risi","submitted_at":"2024-07-07T13:59:46Z","abstract_excerpt":"Human culture relies on collective innovation: our ability to continuously explore how existing elements in our environment can be combined to create new ones. Language is hypothesized to play a key role in human culture, driving individual cognitive capacities and shaping communication. Yet the majority of models of collective innovation assign no cognitive capacities or language abilities to agents. Here, we contribute a computational study of collective innovation where agents are Large Language Models (LLMs) that play Little Alchemy 2, a creative video game originally developed for humans "},"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":"2407.05377","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-07-07T13:59:46Z","cross_cats_sorted":[],"title_canon_sha256":"8a3dca72e0cb6fbc2b637ce042cd3632475eab0336cf564c96a848ab1524953f","abstract_canon_sha256":"95e83e2fe812283f642a8b0a5b4124441ef3a7afe52ae2d9b13de288a05b6e95"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:41:12.177012Z","signature_b64":"3W6cikCHiL9/wTc+uuKfX/7J99KCxc+Bp/eCkOlPPS3zzy6EBKG1Pe12C/P87ppTJKhnwUCIJWvfeIJLR5W3BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0924069d409b6c6e8396be1665d3bd908870696f17f711e093ba513a69fc9743","last_reissued_at":"2026-07-05T08:41:12.176555Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:41:12.176555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Collective Innovation in Groups of Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Cl\\'ement Moulin-Frier, Eleni Nisioti, Ida Momennejad, Pierre-Yves Oudeyer, Sebastian Risi","submitted_at":"2024-07-07T13:59:46Z","abstract_excerpt":"Human culture relies on collective innovation: our ability to continuously explore how existing elements in our environment can be combined to create new ones. Language is hypothesized to play a key role in human culture, driving individual cognitive capacities and shaping communication. Yet the majority of models of collective innovation assign no cognitive capacities or language abilities to agents. Here, we contribute a computational study of collective innovation where agents are Large Language Models (LLMs) that play Little Alchemy 2, a creative video game originally developed for humans "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.05377","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/2407.05377/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":"2407.05377","created_at":"2026-07-05T08:41:12.176621+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.05377v1","created_at":"2026-07-05T08:41:12.176621+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.05377","created_at":"2026-07-05T08:41:12.176621+00:00"},{"alias_kind":"pith_short_12","alias_value":"BESANHKATNWG","created_at":"2026-07-05T08:41:12.176621+00:00"},{"alias_kind":"pith_short_16","alias_value":"BESANHKATNWG5A4W","created_at":"2026-07-05T08:41:12.176621+00:00"},{"alias_kind":"pith_short_8","alias_value":"BESANHKA","created_at":"2026-07-05T08:41:12.176621+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.07544","citing_title":"Position: We Need An Algorithmic Understanding of Generative AI","ref_index":11,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC","json":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC.json","graph_json":"https://pith.science/api/pith-number/BESANHKATNWG5A4WXYLGLU55SC/graph.json","events_json":"https://pith.science/api/pith-number/BESANHKATNWG5A4WXYLGLU55SC/events.json","paper":"https://pith.science/paper/BESANHKA"},"agent_actions":{"view_html":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC","download_json":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC.json","view_paper":"https://pith.science/paper/BESANHKA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.05377&json=true","fetch_graph":"https://pith.science/api/pith-number/BESANHKATNWG5A4WXYLGLU55SC/graph.json","fetch_events":"https://pith.science/api/pith-number/BESANHKATNWG5A4WXYLGLU55SC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC/action/storage_attestation","attest_author":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC/action/author_attestation","sign_citation":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC/action/citation_signature","submit_replication":"https://pith.science/pith/BESANHKATNWG5A4WXYLGLU55SC/action/replication_record"}},"created_at":"2026-07-05T08:41:12.176621+00:00","updated_at":"2026-07-05T08:41:12.176621+00:00"}