{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:CYH2GCN23JN4DOK7MGWLXBHQGD","short_pith_number":"pith:CYH2GCN2","schema_version":"1.0","canonical_sha256":"160fa309bada5bc1b95f61acbb84f030e2dd16b6d6f9524d38ee32f62bee66ce","source":{"kind":"arxiv","id":"2505.18218","version":1},"attestation_state":"computed","paper":{"title":"CoMet: Metaphor-Driven Covert Communication for Multi-Agent Language Games","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Fangwei Zhong, ShuHang Xu","submitted_at":"2025-05-23T08:23:54Z","abstract_excerpt":"Metaphors are a crucial way for humans to express complex or subtle ideas by comparing one concept to another, often from a different domain. However, many large language models (LLMs) struggle to interpret and apply metaphors in multi-agent language games, hindering their ability to engage in covert communication and semantic evasion, which are crucial for strategic communication. To address this challenge, we introduce CoMet, a framework that enables LLM-based agents to engage in metaphor processing. CoMet combines a hypothesis-based metaphor reasoner with a metaphor generator that improves "},"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":"2505.18218","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T08:23:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c203b153bda404b9c54459cb6a9413e9fff44fc0eaa7bbfcac2a86123069277d","abstract_canon_sha256":"7dbbea42cb3e659645b5fa369a92a8bab4a3f33446caac9940679fa3dcd4c8cc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:43.085450Z","signature_b64":"GxeN5/zw+JXJ/4iPSHQz4maWE3euMrGHKnn4G5xPq8lhVFYWslj7Q/bPry3EZ6gPzSzvuckJVPm7JEd7r0CIDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"160fa309bada5bc1b95f61acbb84f030e2dd16b6d6f9524d38ee32f62bee66ce","last_reissued_at":"2026-07-05T11:08:43.084997Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:43.084997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CoMet: Metaphor-Driven Covert Communication for Multi-Agent Language Games","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Fangwei Zhong, ShuHang Xu","submitted_at":"2025-05-23T08:23:54Z","abstract_excerpt":"Metaphors are a crucial way for humans to express complex or subtle ideas by comparing one concept to another, often from a different domain. However, many large language models (LLMs) struggle to interpret and apply metaphors in multi-agent language games, hindering their ability to engage in covert communication and semantic evasion, which are crucial for strategic communication. To address this challenge, we introduce CoMet, a framework that enables LLM-based agents to engage in metaphor processing. CoMet combines a hypothesis-based metaphor reasoner with a metaphor generator that improves "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18218","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/2505.18218/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":"2505.18218","created_at":"2026-07-05T11:08:43.085055+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.18218v1","created_at":"2026-07-05T11:08:43.085055+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18218","created_at":"2026-07-05T11:08:43.085055+00:00"},{"alias_kind":"pith_short_12","alias_value":"CYH2GCN23JN4","created_at":"2026-07-05T11:08:43.085055+00:00"},{"alias_kind":"pith_short_16","alias_value":"CYH2GCN23JN4DOK7","created_at":"2026-07-05T11:08:43.085055+00:00"},{"alias_kind":"pith_short_8","alias_value":"CYH2GCN2","created_at":"2026-07-05T11:08:43.085055+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/CYH2GCN23JN4DOK7MGWLXBHQGD","json":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD.json","graph_json":"https://pith.science/api/pith-number/CYH2GCN23JN4DOK7MGWLXBHQGD/graph.json","events_json":"https://pith.science/api/pith-number/CYH2GCN23JN4DOK7MGWLXBHQGD/events.json","paper":"https://pith.science/paper/CYH2GCN2"},"agent_actions":{"view_html":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD","download_json":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD.json","view_paper":"https://pith.science/paper/CYH2GCN2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.18218&json=true","fetch_graph":"https://pith.science/api/pith-number/CYH2GCN23JN4DOK7MGWLXBHQGD/graph.json","fetch_events":"https://pith.science/api/pith-number/CYH2GCN23JN4DOK7MGWLXBHQGD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD/action/storage_attestation","attest_author":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD/action/author_attestation","sign_citation":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD/action/citation_signature","submit_replication":"https://pith.science/pith/CYH2GCN23JN4DOK7MGWLXBHQGD/action/replication_record"}},"created_at":"2026-07-05T11:08:43.085055+00:00","updated_at":"2026-07-05T11:08:43.085055+00:00"}