{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:I7QQPD6LAAUM4F53QKFFSHE52E","short_pith_number":"pith:I7QQPD6L","schema_version":"1.0","canonical_sha256":"47e1078fcb0028ce17bb828a591c9dd1232935f22ac30d9cb151eb57cee932cc","source":{"kind":"arxiv","id":"2502.07552","version":1},"attestation_state":"computed","paper":{"title":"Unsupervised Translation of Emergent Communication","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Boaz Carmeli, Ido Levy, Orr Paradise, Ron Meir, Shafi Goldwasser, Yonatan Belinkov","submitted_at":"2025-02-11T13:41:06Z","abstract_excerpt":"Emergent Communication (EC) provides a unique window into the language systems that emerge autonomously when agents are trained to jointly achieve shared goals. However, it is difficult to interpret EC and evaluate its relationship with natural languages (NL). This study employs unsupervised neural machine translation (UNMT) techniques to decipher ECs formed during referential games with varying task complexities, influenced by the semantic diversity of the environment. Our findings demonstrate UNMT's potential to translate EC, illustrating that task complexity characterized by semantic divers"},"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":"2502.07552","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T13:41:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e4606d88a0a9dbd17934294154abc3e9d2004be13d84988d1a0a9ff8adf4b77e","abstract_canon_sha256":"52f33375b0e3516eb902709b04c35f0b61b5d3ef5b761c346fa256e48155225b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:12:39.104416Z","signature_b64":"IJV51R8LohMxFbVNd4a6Ko9+erhRYfTBSuR4L1TAPGpDOoSJokoiBCCnILqApVVbVFPHK9SNqEjJ2eRqo5kBDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47e1078fcb0028ce17bb828a591c9dd1232935f22ac30d9cb151eb57cee932cc","last_reissued_at":"2026-07-05T10:12:39.103989Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:12:39.103989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unsupervised Translation of Emergent Communication","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Boaz Carmeli, Ido Levy, Orr Paradise, Ron Meir, Shafi Goldwasser, Yonatan Belinkov","submitted_at":"2025-02-11T13:41:06Z","abstract_excerpt":"Emergent Communication (EC) provides a unique window into the language systems that emerge autonomously when agents are trained to jointly achieve shared goals. However, it is difficult to interpret EC and evaluate its relationship with natural languages (NL). This study employs unsupervised neural machine translation (UNMT) techniques to decipher ECs formed during referential games with varying task complexities, influenced by the semantic diversity of the environment. Our findings demonstrate UNMT's potential to translate EC, illustrating that task complexity characterized by semantic divers"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.07552","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/2502.07552/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":"2502.07552","created_at":"2026-07-05T10:12:39.104051+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.07552v1","created_at":"2026-07-05T10:12:39.104051+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.07552","created_at":"2026-07-05T10:12:39.104051+00:00"},{"alias_kind":"pith_short_12","alias_value":"I7QQPD6LAAUM","created_at":"2026-07-05T10:12:39.104051+00:00"},{"alias_kind":"pith_short_16","alias_value":"I7QQPD6LAAUM4F53","created_at":"2026-07-05T10:12:39.104051+00:00"},{"alias_kind":"pith_short_8","alias_value":"I7QQPD6L","created_at":"2026-07-05T10:12:39.104051+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E","json":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E.json","graph_json":"https://pith.science/api/pith-number/I7QQPD6LAAUM4F53QKFFSHE52E/graph.json","events_json":"https://pith.science/api/pith-number/I7QQPD6LAAUM4F53QKFFSHE52E/events.json","paper":"https://pith.science/paper/I7QQPD6L"},"agent_actions":{"view_html":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E","download_json":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E.json","view_paper":"https://pith.science/paper/I7QQPD6L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.07552&json=true","fetch_graph":"https://pith.science/api/pith-number/I7QQPD6LAAUM4F53QKFFSHE52E/graph.json","fetch_events":"https://pith.science/api/pith-number/I7QQPD6LAAUM4F53QKFFSHE52E/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E/action/storage_attestation","attest_author":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E/action/author_attestation","sign_citation":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E/action/citation_signature","submit_replication":"https://pith.science/pith/I7QQPD6LAAUM4F53QKFFSHE52E/action/replication_record"}},"created_at":"2026-07-05T10:12:39.104051+00:00","updated_at":"2026-07-05T10:12:39.104051+00:00"}