{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:54ZXNISO2WLNQDKCPJGWQZX4I7","short_pith_number":"pith:54ZXNISO","schema_version":"1.0","canonical_sha256":"ef3376a24ed596d80d427a4d6866fc47cbfcd206ed109cdaac263decc3c54d02","source":{"kind":"arxiv","id":"2205.12392","version":2},"attestation_state":"computed","paper":{"title":"Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Akira Taniguchi, Tadahiro Taniguchi, Yoshinobu Hagiwara, Yuto Yoshida","submitted_at":"2022-05-24T22:49:53Z","abstract_excerpt":"Constructive studies on symbol emergence systems seek to investigate computational models that can better explain human language evolution, the creation of symbol systems, and the construction of internal representations. This study provides a new model for emergent communication, which is based on a probabilistic generative model (PGM) instead of a discriminative model based on deep reinforcement learning. We define the Metropolis-Hastings (MH) naming game by generalizing previously proposed models. It is not a referential game with explicit feedback, as assumed by many emergent communication"},"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":"2205.12392","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-05-24T22:49:53Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"bb71714b59db1c41ddf91359069bf5927a7f4a7346866769d121795f6778132d","abstract_canon_sha256":"d01f26106f06e570cd5b36c623ecad70650926cec797e22cc7b5d52b9bf845cc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:33:11.118712Z","signature_b64":"AlKAL+JkXeud3nAcIw9U4/hmbasTdlWj6O1k3Htz7jM8OxuomRI9K2HFRAm6APaiT+kQKTnKRQMcuTwF28RpBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef3376a24ed596d80d427a4d6866fc47cbfcd206ed109cdaac263decc3c54d02","last_reissued_at":"2026-07-05T05:33:11.118265Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:33:11.118265Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Akira Taniguchi, Tadahiro Taniguchi, Yoshinobu Hagiwara, Yuto Yoshida","submitted_at":"2022-05-24T22:49:53Z","abstract_excerpt":"Constructive studies on symbol emergence systems seek to investigate computational models that can better explain human language evolution, the creation of symbol systems, and the construction of internal representations. This study provides a new model for emergent communication, which is based on a probabilistic generative model (PGM) instead of a discriminative model based on deep reinforcement learning. We define the Metropolis-Hastings (MH) naming game by generalizing previously proposed models. It is not a referential game with explicit feedback, as assumed by many emergent communication"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12392","kind":"arxiv","version":2},"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/2205.12392/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":"2205.12392","created_at":"2026-07-05T05:33:11.118323+00:00"},{"alias_kind":"arxiv_version","alias_value":"2205.12392v2","created_at":"2026-07-05T05:33:11.118323+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12392","created_at":"2026-07-05T05:33:11.118323+00:00"},{"alias_kind":"pith_short_12","alias_value":"54ZXNISO2WLN","created_at":"2026-07-05T05:33:11.118323+00:00"},{"alias_kind":"pith_short_16","alias_value":"54ZXNISO2WLNQDKC","created_at":"2026-07-05T05:33:11.118323+00:00"},{"alias_kind":"pith_short_8","alias_value":"54ZXNISO","created_at":"2026-07-05T05:33:11.118323+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.15721","citing_title":"On Parallelism in Music and Language: A Perspective from Symbol Emergence Systems based on Probabilistic Generative Models","ref_index":69,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7","json":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7.json","graph_json":"https://pith.science/api/pith-number/54ZXNISO2WLNQDKCPJGWQZX4I7/graph.json","events_json":"https://pith.science/api/pith-number/54ZXNISO2WLNQDKCPJGWQZX4I7/events.json","paper":"https://pith.science/paper/54ZXNISO"},"agent_actions":{"view_html":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7","download_json":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7.json","view_paper":"https://pith.science/paper/54ZXNISO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2205.12392&json=true","fetch_graph":"https://pith.science/api/pith-number/54ZXNISO2WLNQDKCPJGWQZX4I7/graph.json","fetch_events":"https://pith.science/api/pith-number/54ZXNISO2WLNQDKCPJGWQZX4I7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7/action/storage_attestation","attest_author":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7/action/author_attestation","sign_citation":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7/action/citation_signature","submit_replication":"https://pith.science/pith/54ZXNISO2WLNQDKCPJGWQZX4I7/action/replication_record"}},"created_at":"2026-07-05T05:33:11.118323+00:00","updated_at":"2026-07-05T05:33:11.118323+00:00"}